PREMIER UNIVERSITY
Department of Computer Science And Engineering
PREMIER UNIVERSITY
Department of Computer Science And Engineering
CSE OBE Curriculum (Old)
The curriculum of the program offers 144 credits of Required courses and 16 credits of Elective courses including basic science, language, mathematics, core, and non-engineering categories. The following table shows the breakdown of the curriculum of the program.
|
Category |
Required |
Elective |
|
Basic Science |
06 Credits |
|
|
Language |
07 Credits |
|
|
Mathematics |
12 Credits |
|
|
Core |
107 Credits |
16 Credits |
|
Non-Engineering |
12 Credits |
Program Educational Objectives (PEO): Within 3-5 years of graduation, the graduates of CSE will be able to:
PEO-1: Think Critically: Use problem-solving, decision-making and research skills to identify and solve complex problems needed to pursue a diverse range of professions.
PEO-2: Implementation Efficiency: Develop and implement efficient, sustainable, scalable, manageable, and future-proof solutions to problems through continuous learning.
PEO-3: Society, Ethics and Team Player: ethically manage independent or team work considering the societal, health and safety, and environmental impact.
PEO-4: Communication: Graduates will be able to disseminate information clearly and precisely to a broad range of audiences.
|
Missions |
PEO-1 |
PEO-2 |
PEO-3 |
PEO-4 |
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Mission 2: |
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Mission 3: |
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Mission 4: |
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Mission 5: |
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Mission 6: |
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Mission 7: |
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The BS-CSE has twelve program outcomes adopted from the preferred outcomes of both Computing Accreditation Commission (CAC) and Engineering Accreditation Commission (ECA) of ABET. The students who complete the BSc-CSE program will have:
PO1: Engineering knowledge: Apply knowledge of mathematics, natural science, engineering fundamentals and an engineering specialization as specified in K1 to K4 respectively to the solution of complex engineering problems.
PO2: Problem analysis: Identify, formulate, research literature and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences. (K1 to K4)
PO3: Design/development of solutions: Design solutions for complex engineering problems and design systems, components or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations. (K5)
PO4: Conduct investigations of complex problems: Conduct investigations of complex problems using research-based knowledge (K8) and research methods including design of experiments, analysis and interpretation of data, and synthesis of information to provide valid conclusions.
PO5: Modern tool usage: Create, select and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering problems, with an understanding of the limitations. (K6)
PO6: The engineer and society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice and solutions to complex engineering problems. (K7)
PO7: Environment and sustainability: Understand and evaluate the sustainability and impact of professional engineering work in the solution of complex engineering problems in societal and environmental contexts. (K7)
PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice. (K7)
PO9: Individual work and teamwork: Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings.
PO10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO11: Project management and finance: Demonstrate knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
|
PO No. |
PO Statement |
PEO-1 |
PEO-2 |
PEO-3 |
PEO-4 |
|
Thinking Critically |
Implement Efficiently |
Society, Ethics, and Team Player |
Communication |
||
|
PO1 |
Engineering Knowledge |
√ |
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|
PO2 |
Problem Analysis |
√ |
|||
|
PO3 |
Design/ Development of Solutions |
√ |
√ |
√ |
|
|
PO4 |
Conduct investigations of complex problems |
√ |
|||
|
PO5 |
Modern Tool Usage |
√ |
√ |
||
|
PO6 |
The Engineer and Society |
√ |
|||
|
PO7 |
Environment and Sustainability |
√ |
√ |
||
|
PO8 |
Ethics |
√ |
|||
|
PO9 |
Individual and Team Work |
√ |
√ |
||
|
PO10 |
Communication |
√ |
√ |
||
|
PO11 |
Project Management and Finance |
√ |
|||
|
PO12 |
Life-long Learning |
√ |
The knowledge profile should have eight attributes (K1 to K8), indicating the volume of learning and attributes against which graduates must be able to perform.
K1: A systematic, theory-based understanding of the natural sciences applicable to the discipline
K2: Conceptually-based mathematics, numerical analysis, statistics and formal aspects of computer and information science to support analysis and modelling applicable to the discipline
K3: A systematic, theory-based formulation of engineering fundamentals required in the engineering discipline
K4: Engineering specialist knowledge that provides theoretical frameworks and bodies of knowledge for the accepted practice areas in the engineering discipline; much is at the forefront of the discipline.
K5: Knowledge that supports engineering design in a practice area
K6: Knowledge of engineering practice (technology) in the practice areas in the engineering discipline
K7: Comprehension of the role of engineering in society and identified issues in engineering practice in the discipline: ethics and the professional responsibility of an engineer to public safety; the impacts of engineering activity: economic, social, cultural, environmental and sustainability
K8: Engagement with selected knowledge in the research literature of the discipline
A program that builds this type of knowledge and develops the attributes listed above is typically achieved in 4 to 5 years of study, depending on the level of students at entry.
Complex engineering problems are those that include a wide range of or conflicting technical, engineering, and other challenges, have no clear solution, and necessitate analytical thinking and originality in analysis to design effective models. The ability to solve complicated problems in engineering is vital in the engineering curriculum. The list of complex engineering problems (P1 to P7) clarifies the concept of Complex Engineering Problem by establishing seven problem-solving ranges or features.
P1- (Depth of knowledge required) Cannot be resolved without in-depth engineering knowledge at the level of one or more of K3, K4, K5, K6 or K8 which allows a fundamentals-based, first principles analytical approach.
P2- (Range of conflicting requirements) Involve wide-ranging or conflicting technical, engineering and other issues.
P3- (Depth of analysis required) Have no obvious solution and require abstract thinking, originality in analysis to formulate suitable models.
P4- (Familiarity of issues) Involve infrequently encountered issues
P5- (Extent of applicable codes) Are outside problems encompassed by standards and codes of practice for professional engineering.
P6- (Extent of stakeholder involvement and conflicting requirements) Involve diverse groups of stakeholders with widely varying needs.
P7- (Interdependence) Are high level problems including many component parts or sub-problems.
There are five attributes of activities students can be involved in when solving Complex Engineering Problem. A Complex Engineering Activity or Project is that which has some or all of the following attributes:
A1- (Range of resources) Involve the use of diverse resources (and for this purpose resources include people, money, equipment, materials, information and technologies).
A2- (Level of interaction) Require resolution of significant problems arising from interactions between wide-ranging or conflicting technical, engineering or other issues.
A3- (Innovation) Involve creative use of engineering principles and research-based knowledge in novel ways.
A4- (Consequences for society and the environment) Have significant consequences in a range of contexts, characterized by difficulty of prediction and mitigation.
A5- (Familiarity) Can extend beyond previous experiences by applying principles-based approaches
| Level | Cognitive (C) | Affective (A) | Psychomotor (P) |
|---|---|---|---|
| 1 | Remember | Receive | Imitation |
| 2 | Understand | Respond | Manipulation |
| 3 | Apply | Value | Precision |
| 4 | Analyze | Organization | Articulation |
| 5 | Evaluate | Characterization | Naturalization |
| 6 | Create | - | - |
Basic Science (6 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
PHY 101 |
Engineering Physics I |
3 |
|
2 |
PHY 103 |
Engineering Physics II |
3 |
Language (7 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
ENG 101 |
General English |
3 |
|
2 |
ENG 103 |
Developing English Skills |
2 |
|
3 |
ENG 401 |
Technical Writing & Presentation |
2 |
Mathematics (12 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
MAT 105 |
Engineering Mathematics I |
3 |
|
2 |
MAT 107 |
Engineering Mathematics II |
3 |
|
3 |
MAT 201 |
Engineering Mathematics III |
3 |
|
4 |
MAT 203 |
Engineering Mathematics IV |
3 |
Core (107 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
CSE 110 |
Introduction to Computer Systems (Laboratory) |
2 |
|
2 |
EEE 101 |
Electrical Circuits I |
3 |
|
3 |
EEE 102 |
Electrical Circuits I Laboratory |
1.5 |
|
4 |
ME 102 |
Mechanical Engineering Drawing & CAD (Laboratory) |
1 |
|
5 |
CSE 103 |
Discrete Mathematics |
3 |
|
6 |
CSE 111 |
Structured Programming |
2 |
|
7 |
CSE 112 |
Structured Programming Laboratory |
2 |
|
8 |
EEE 211 |
Electronics I |
3 |
|
9 |
EEE 212 |
Electronics I Laboratory |
1.5 |
|
10 |
CSE 211 |
Object Oriented Programming |
3 |
|
11 |
CSE 212 |
Object Oriented Programming Laboratory |
1.5 |
|
12 |
CSE 221 |
Data Structures |
3 |
|
13 |
CSE 222 |
Data Structures Laboratory |
1.5 |
|
14 |
EEE 311 |
Digital Electronics |
3 |
|
15 |
EEE 312 |
Digital Electronics Laboratory |
1.5 |
|
16 |
CSE 225 |
Algorithm Design and Analysis |
3 |
|
17 |
CSE 226 |
Algorithm Design and Analysis Laboratory |
1 |
|
18 |
CSE 237 |
Database Management Systems |
3 |
|
19 |
CSE 238 |
Database Management Systems Laboratory |
1.5 |
|
20 |
EEE 201 |
Signals & Systems |
3 |
|
21 |
EEE 202 |
Signals & Systems Laboratory |
1 |
|
22 |
CSE 301 |
Computational Methods for Engineering Problems |
3 |
|
23 |
CSE 302 |
Computational Methods for Engineering Problems Laboratory |
1 |
|
24 |
CSE 305 |
Software Engineering & Information System Design |
4 |
|
25 |
CSE 306 |
Software Engineering & Information System Design Laboratory |
1.5 |
|
26 |
EEE 309 |
Communication Engineering |
3 |
|
27 |
EEE 310 |
Communication Engineering Laboratory |
1.5 |
|
28 |
EEE 371 |
Microprocessors & Microcontrollers |
3 |
|
29 |
EEE 372 |
Microprocessors & Microcontrollers Laboratory |
1.5 |
|
30 |
CSE 317 |
Artificial Intelligence |
3 |
|
31 |
CSE 318 |
Artificial Intelligence Laboratory |
1.5 |
|
32 |
CSE 333 |
Operating Systems |
3 |
|
33 |
CSE 334 |
Operating Systems Laboratory |
1.5 |
|
34 |
CSE 337 |
Computer Organization & Architecture |
3 |
|
35 |
CSE 338 |
Software Development Project (Laboratory) |
2 |
|
36 |
CSE 363 |
Data Communication |
3 |
|
37 |
CSE 367 |
Computer Networks |
3 |
|
38 |
CSE 368 |
Computer Networks Laboratory |
1.5 |
|
39 |
EEE 313 |
Control Systems |
3 |
|
40 |
EEE 314 |
Control Systems Laboratory |
1.5 |
|
41 |
CSE 309 |
Theory of Computation |
2 |
|
42 |
CSE 451 |
Neural Network & Fuzzy Logic |
3 |
|
43 |
CSE 452 |
Neural Network & Fuzzy Logic Laboratory |
1 |
|
44 |
CSE 437 |
Network and Computer Security |
3 |
|
45 |
CSE 453 |
Compiler Construction |
3 |
|
46 |
CSE 454 |
Compiler Construction Laboratory |
1.5 |
|
47 |
CSE 400 |
Project/Thesis |
4 |
Non-Engineering (12 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
ACC 101 |
Basic Accounting |
3 |
|
2 |
ECO 201 |
Basic Economics |
3 |
|
3 |
MGT 203 |
Industrial and Business Management |
3 |
|
4 |
MGT 251 |
Organizational Behavior |
3 |
Electives (16 credits)
|
SL. |
Course Code |
Course Title |
Credit Hour |
|
1 |
CSE 455 |
Computer Graphics & Image Processing (Elective) |
3 |
|
2 |
CSE 456 |
Computer Graphics & Image Processing Laboratory (Elective) |
1 |
|
3 |
CSE 457 |
Machine Learning (Elective) |
3 |
|
4 |
CSE 458 |
Machine Learning Laboratory (Elective) |
1 |
|
5 |
CSE 455 |
Complementary Computer Course (Elective) |
3 |
|
6 |
CSE 456 |
Complementary Computer Course (Elective) |
1 |
|
7 |
CSE 459 |
Pattern Recognition (Elective) |
3 |
|
8 |
CSE 460 |
Pattern Recognition Laboratory (Elective) |
1 |
Distribution of Courses
Term-wise course outline for the entire program:
|
Level one Term one |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
ACC 101 |
Basic Accounting |
3 |
3 |
|
CSE 110 |
Introduction to Computer Systems (Laboratory) |
2 |
4 |
|
EEE 101 |
Electrical Circuits I |
3 |
3 |
|
EEE 102 |
Electrical Circuits I Laboratory |
1.5 |
3 |
|
ENG 101 |
General English |
3 |
3 |
|
MAT 105 |
Engineering Mathematics I |
3 |
3 |
|
ME 102 |
Mechanical Engineering Drawing & CAD (Laboratory) |
1 |
2 |
|
PHY 101 |
Engineering Physics I |
3 |
3 |
|
Total |
Theory: 5 Sessional: 3 |
19.5 |
24 |
|
Level one Term two |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 103 |
Discrete Mathematics |
3 |
3 |
|
CSE 111 |
Structured Programming |
2 |
2 |
|
CSE 112 |
Structured Programming Laboratory |
2 |
4 |
|
EEE 211 |
Electronics I |
3 |
3 |
|
EEE 212 |
Electronics I Laboratory |
1.5 |
3 |
|
ENG 103 |
Developing English Skills |
2 |
2 |
|
MAT 107 |
Engineering Mathematics II |
3 |
3 |
|
PHY 103 |
Engineering Physics II |
3 |
3 |
|
Total |
Theory: 6 Sessional: 2 |
19.5 |
23 |
|
Level two Term one |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 211 |
Object Oriented Programming |
3 |
3 |
|
CSE 212 |
Object Oriented Programming Laboratory |
1.5 |
3 |
|
CSE 221 |
Data Structures |
3 |
3 |
|
CSE 222 |
Data Structures Laboratory |
1.5 |
3 |
|
ECO 201 |
Basic Economics |
3 |
3 |
|
EEE 311 |
Digital Electronics |
3 |
3 |
|
EEE 312 |
Digital Electronics Laboratory |
1.5 |
3 |
|
MAT 201 |
Engineering Mathematics III |
3 |
3 |
|
Total |
Theory: 5 Sessional: 3 |
19.5 |
24 |
|
Level two Term two |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 225 |
Algorithm Design and Analysis |
3 |
3 |
|
CSE 226 |
Algorithm Design and Analysis Laboratory |
1 |
2 |
|
CSE 237 |
Database Management Systems |
3 |
3 |
|
CSE 238 |
Database Management Systems Laboratory |
1.5 |
3 |
|
EEE 201 |
Signals & Systems |
3 |
3 |
|
EEE 202 |
Signals & Systems Laboratory |
1 |
2 |
|
MAT 203 |
Engineering Mathematics IV |
3 |
3 |
|
MGT 203 |
Industrial and Business Management |
3 |
3 |
|
Total |
Theory: 5 Sessional: 3 |
18.5 |
22 |
|
Level three Term one |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 301 |
Computational Methods for Engineering Problems |
3 |
3 |
|
CSE 302 |
Computational Methods for Engineering Problems Laboratory |
1 |
2 |
|
CSE 305 |
Software Engineering & Information System Design |
4 |
4 |
|
CSE 306 |
Software Engineering & Information System Design Laboratory |
1.5 |
3 |
|
EEE 309 |
Communication Engineering |
3 |
3 |
|
EEE 310 |
Communication Engineering Laboratory |
1.5 |
3 |
|
EEE 371 |
Microprocessors & Microcontrollers |
3 |
3 |
|
EEE 372 |
Microprocessors & Microcontrollers Laboratory |
1.5 |
3 |
|
MGT 251 |
Organizational Behavior |
3 |
3 |
|
Total |
Theory: 5 Sessional: 4 |
21.5 |
27 |
|
Level three Term two |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 317 |
Artificial Intelligence |
3 |
3 |
|
CSE 318 |
Artificial Intelligence Laboratory |
1.5 |
3 |
|
CSE 333 |
Operating Systems |
3 |
3 |
|
CSE 334 |
Operating Systems Laboratory |
1.5 |
3 |
|
CSE 337 |
Computer Organization & Architecture |
3 |
3 |
|
CSE 338 |
Software Development Project (Laboratory) |
2 |
4 |
|
CSE 364 |
Data Communication |
3 |
3 |
|
CSE 367 |
Computer Networks |
3 |
3 |
|
CSE 368 |
Computer Networks Laboratory |
1.5 |
3 |
|
Total |
Theory: 5 Sessional: 4 |
21.5 |
26 |
|
Level four Term one |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
EEE 313 |
Control Systems |
3 |
3 |
|
EEE 314 |
Control Systems Laboratory |
1.5 |
3 |
|
ENG 401 |
Technical Writing & Presentation |
2 |
2 |
|
CSE 309 |
Theory of Computation |
2 |
2 |
|
CSE 451 |
Neural Network & Fuzzy Logic |
3 |
3 |
|
CSE 452 |
Neural Network & Fuzzy Logic Laboratory |
1 |
2 |
|
CSE 455 |
Computer Graphics & Image Processing (Elective) |
3 |
3 |
|
CSE 456 |
Computer Graphics & Image Processing Laboratory (Elective) |
1 |
2 |
|
CSE 437 |
Network and Computer Security |
3 |
3 |
|
Total |
Theory: 6, Sessional: 3 |
19.5 |
23 |
|
Level four Term two |
|||
|
Course No. |
Course Title |
Credit Hours |
Contact Hours |
|
CSE 453 |
Compiler Construction |
3 |
3 |
|
CSE 454 |
Compiler Construction Laboratory |
1.5 |
3 |
|
CSE 457 |
Machine Learning (Elective) |
3 |
3 |
|
CSE 458 |
Machine Learning Laboratory (Elective) |
1 |
2 |
|
CSE 481 |
Contemporary Courses of Computer Course (Elective) |
3 |
3 |
|
CSE 482 |
Contemporary Courses of Computer Course Laboratory (Elective) |
1 |
2 |
|
CSE 459 |
Pattern Recognition (Elective) |
3 |
3 |
|
CSE 460 |
Pattern Recognition Laboratory (Elective) |
1 |
2 |
|
CSE 400 |
Project/Thesis |
4 |
4 |
|
Total |
Theory: 4 Sessional: 5 |
20.5 |
25 |
Four Optional courses (Theory + Lab) have to be selected from the list given below:
| CSE 411 | Project Management for Information Systems | 3 |
| CSE 412 | Project Management for Information Systems Laboratory | 1 |
| CSE 417 | Advanced Software Engineering | 3 |
| CSE 418 | Advanced Software Engineering Laboratory | 1 |
| CSE 451 | Neural Network & Fuzzy Logic | 3 |
| CSE 452 | Neural Network & Fuzzy Logic Laboratory | 1 |
| EEE 319 | Telecommunication & Switching | 3 |
| EEE 320 | Telecommunication & Switching Laboratory | 1 |
| EEE 403 | Microwave & Antenna Engineering | 3 |
| EEE 404 | Microwave & Antenna Engineering Laboratory | 1 |
| EEE 435 | Cellular Mobile Communication | 3 |
| EEE 469 | Optical Fiber Communication | 3 |
| EEE 470 | Optical Fiber Communication Laboratory | 1 |
| CSE 431 | Wireless Technologies | 3 |
| CSE 432 | Wireless Technologies Laboratory | 1 |
| CSE 433 | Advanced Switching & Routing Concepts | 3 |
| CSE 434 | Advanced Switching & Routing Concepts Laboratory | 1 |
| CSE 435 | WAN Technologies | 3 |
| CSE 436 | WAN Technologies Laboratory | 1 |
| CSE 415 | Human Computer Interaction | 3 |
| CSE 416 | Human Computer Interaction Laboratory | 1 |
| CSE 419 | Basic Multimedia Systems | 3 |
| CSE 420 | Basic Multimedia Systems Laboratory | 1 |
| CSE 455 | Computer Graphics & Image Processing | 3 |
| CSE 456 | Computer Graphics & Image Processing Laboratory | 1 |
| CSE 457 | Machine Learning | 3 |
| CSE 458 | Machine Learning Laboratory | 1 |
| CSE 459 | Pattern Recognition | 3 |
| CSE 460 | Pattern Recognition Laboratory | 1 |
| CSE 461 | Management Information System | 3 |
| CSE 462 | Management Information System Laboratory | 1 |
| CSE 463 | Graph Theory | 3 |
| CSE 464 | Graph Theory Laboratory | 1 |
| CSE 465 | Distributed AI and Intelligent Agent | 3 |
| CSE 466 | Distributed AI and Intelligent Agent Laboratory | 1 |
| CSE 467 | Parallel & Distributed Computing | 3 |
| CSE 468 | Parallel & Distributed Computing Laboratory | 1 |
| CSE 471 | VoIP | 3 |
| CSE 472 | VoIP Laboratory | 1 |
| CSE 477 | Computer Interfacing | 3 |
| CSE 478 | Computer Interfacing Laboratory | 1 |
| CSE 481 | Computational Geometry | 3 |
| CSE 482 | Computational Geometry Laboratory | 1 |
| CSE 483 | Digital System Design | 3 |
| CSE 484 | Digital System Design Laboratory | 1 |
| EEE 443 | VLSI Design | 3 |
| EEE 444 | VLSI Design Laboratory | 1 |
| EEE 455 | Satellite Communication | 3 |
| EEE 456 | Satellite Communication Laboratory | 1 |
| EEE 477 | Digital Signal Processing | 3 |
| EEE 478 | Digital Signal Processing Laboratory | 1 |
| CSE 485 | Contemporary course of Computer Science I | 3 |
| CSE 486 | Contemporary course of Computer Science I Laboratory | 1 |
| CSE 487 | Contemporary course of Computer Science II | 3 |
| CSE 488 | Contemporary course of Computer Science II Laboratory | 1 |
- Discrete Mathematics (CSE 103)
- Structured Programming (CSE 111)
- Structured Programming Lab (CSE 112)
- Algorithm Design and Analysis (CSE 225)
- Algorithm Design and Analysis Lab (CSE 226)
- Software Engineering and Information System Design (CSE 305)
- Software Engineering and Information System Design Lab (CSE 306)
- Microprocessor and Microcontroller (EEE 371)
- Microprocessor and Microcontroller Lab (EEE 372)
- Artificial Intelligence (CSE 317)
- Artificial Intelligence Lab (CSE 318)
- Software Development (CSE 338)
- Computer Networks (CSE 367)
- Computer Networks Lab (CSE 368)
- Project/Thesis (CSE 400)
| Course Code | Program Outcomes | Knowledge Profile | Complex Engineering Problem Solving | Complex Engineering Activities | ||||||||||||||||||||||||||||
| PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 | K1 | K2 | K3 | K4 | K5 | K6 | K7 | K8 | EP1 | EP2 | EP3 | EP4 | EP5 | EP6 | EP7 | EA1 | EA2 | EA3 | EA4 | EA5 | |
| K1-K4 | K5 | K8 | K6 | K7 | K7 | Related to PO10 | ||||||||||||||||||||||||||
| Complex Engineering Problem Solution | ||||||||||||||||||||||||||||||||
| Engineering Knowledge | Problem Analysis | Design/development to solutions | Investigation | Modern tool usage | The engineer and society | Environment and sustainability | Ethics | Indivdual work and team work | Communication | Project management and finance | Life-long Learning | Science | Math | Engg. Fundamentals | Engg. Specialization | Design | Technology | Society | Research | Knowledge k3-k6,k8 | Wide ranging/ Conflicting | Depth of analysis | Familiarity of issues | Extent of applicable codes | Extent of stakeholders | Interdependencce | Range of resources | Level of interaction | Innovation | Consequences | Familiarity | |
| CSE 111 (SP) | √ | √ | √ | √ | √ | |||||||||||||||||||||||||||
| CSE 112 (SPL) | √ | √ | √ | √ | √ | √ | √ | √ | √ | |||||||||||||||||||||||
| CSE 103 (DM) | √ | √ | √ | √ | √ | √ | ||||||||||||||||||||||||||
| CSE 225 (ADA) | √ | √ | √ | √ | ||||||||||||||||||||||||||||
| CSE 226 (ADAL) | √ | √ | √ | √ | ||||||||||||||||||||||||||||
| CSE 305 (SEISD) | √ | √ | √ | √ | √ | |||||||||||||||||||||||||||
| CSE 306 (SEISDL) | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | ||||||||||||||||||||||
| EEE 371 (MM) | √ | √ | √ | √ | ||||||||||||||||||||||||||||
| EEE 372 (MML) | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | |||||||
| CSE 317 (AI) | √ | √ | √ | √ | √ | √ | ||||||||||||||||||||||||||
| CSE 318 (AIL) | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | ||||||||||||||||||||||
| CSE 338 (SD) | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | |||
| CSE 367 (CN) | √ | √ | √ | √ | √ | |||||||||||||||||||||||||||
| CSE 368 (CNL) | √ | √ | √ | √ | √ | √ | √ | √ | √ | |||||||||||||||||||||||
| CSE 400 (Thesis/ Project) | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ | |
Course Title: Engineering Physics I
Course Code: PHY 101
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Basic Science | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is intended to build up strong base in mechanics, waves and oscillations, and thermal science as well as to include the experience of applications of its contents in the relevant courses of science/engineering.
Course Objectives:
The objectives of this course are:
- To enhance the understanding and problem-solving skills on related/necessary basic topics in mechanics, waves and oscillations, and thermal science required for learning the related topics in the courses of undergraduate program in computer science and engineering.
- To develop the basic concepts of mechanics, waves and oscillations, and thermal science in their relevant scope.
- To builds up problem solving experience in each relevant topic along with addition of application familiarity in the related areas of science/engineering. Etc.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Identify (C1) typical simple and moderately complex problems of selected topics and of the linked topics of science/engineering courses of undergraduate programs; |
|
CO2 |
Develop (C2) mathematical expressions of different physical laws of knowledge and skills acquired in the related more advanced courses. |
|
CO3 |
Apply (C3) different physical laws for solving related unusual/advanced problems. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Mechanics: Kinematics, Graphical representations of displacement-time, velocity-time and acceleration-time. |
CO1 |
|
2. |
Motion in two and three dimensions-projectile motion, Application of Newton’s laws of motion; Equilibrium forces. Work-kinetic energy theorem. Power; Conservation of energy, Conservation of linear momentum for a system of particles. Center-of-mass motion. Elastic and inelastic collision in one dimension, Gravitation: Gravitational field, Kepler’s laws |
CO1, CO2, CO3 |
|
3. |
Waves & Oscillations: Simple Harmonic motion, damped simple harmonic oscillation, forced oscillations, Combination and Composition of simple harmonic motions, Lissajous figures, Transverse and Longitudinal nature of waves, traveling and standing waves, intensity of waves, Energy calculation of progressive & stationary waves, Phase velocity, group velocity, Velocity of Longitudinal wave in a gaseous medium, Doppler effect. |
CO1, CO2, CO3 |
|
4. |
Thermodynamics: Heat and temperature. Zeroth and 1st law of thermodynamics, Isothermal and adiabatic relations, Second law of thermodynamics. Reversible and irreversible processes, Carnot cycle, Auto cycle, Diesel cycle and their efficiency, Clausius theorem. Entropy. Absolute scale of temperature. Clausius Clapeyron equation. Thermodynamic functions, Maxwell’s thermodynamic relations. Problem involving thermodynamic relations and functions. Gibb’s phase rule |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
- An Introduction to Mechanics by Daniel Kleppner, Robert Kolenkow
- A text book of Sound by Brij Lal and N. Subrahmanyam
- A Textbook of Heat by M. N. Saha and B. N. Srivastava
- Heat and Thermodynamics by Brij Lal and N. Subrahmanyam
- Physics for Engineers Part 1 by Dr. Giasuddin Ahmed
- Physics Vol. 1 by Robert Resnick, David Halliday, Kenneth S. Krane
- Heat and Thermodynamics: An Intermediate Textbook by Richard H.Dittman and
Mark W. Zemansky - Acoustics & Vibrational Physics by Stephenson
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C1 |
Lecture notes, PPT slides, problem solving, web content |
Assignment, Class Test, Midterm, Final exam |
|
CO2 |
PO1 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Assignment, Class Test, Midterm, Final exam |
|
CO3 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Assignment, Class Test, Midterm, Final exam |
Course Title: Engineering Physics II
Course Code: PHY 103
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Basic Science | Pre-requisite: EP I |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is intended to build up strong base in electromagnetism, optics, and modern physics, as well as to include the experience of applications of its contents in the relevant courses of science/engineering.
Course Objectives:
- This course enhances the understanding and problem-solving skills on related/necessary basic topics in electromagnetism, optics and modern physics required for learning the related topics in the courses of undergraduate program in computer science and engineering.
- Toward the above goal, it develops the basic concepts of electromagnetism, optics, and modern physics in their relevant scope.
- While doing the above it builds up problem solving experience in each relevant topic along with addition of application familiarity in the related areas of science/engineering. Etc.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Identify (C1) typical simple and moderately complex problems of selected topics and of the linked topics of science/engineering courses of undergraduate programs; |
|
CO2 |
Develop (C2) mathematical expressions of different physical laws of knowledge and skills acquired in the related more advanced courses. |
|
CO3 |
Apply (C3) different physical laws for solving related unusual/advanced problems. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Electricity and Magnetism: Electromagnetism: Magnetic fields, Maxwell’s equations, Ampere’s law, Faraday’s law, Lenz’s law. Inductance: Self mutual inductance. |
CO1, CO2, CO3 |
|
2. |
Magnetic properties of matter: Magnetomotive force, magnetic field intensity, permeability and susceptibility |
CO1, CO2, CO3 |
|
3. |
classification of magnetic materials, magnetization curve of ferromagnetic materials, magnetic circuits, magnetostriction; |
CO1, CO2, CO3 |
|
4. |
Optics: Theories of light; Huygen’s principles and constructions; |
CO1, CO2, CO3 |
|
5. |
Interference of light: Young’s double slit experiment, Fresnel bi-prism, Newton’s ring, interferometers |
CO1, CO2, CO3 |
|
6. |
Diffraction of light: Diffraction, Fresnel Fraunhoffer diffraction, Diffraction by single slit, Diffraction by double slit, |
CO1, CO2, CO3 |
|
7. |
Polarization of light: Polarization of electromagnetic waves, production and analysis of polarized light, optical activity, Optics of crystals; |
CO1, CO2, CO3 |
|
8. |
Lasers and their Applications: Laser introduction, Stimulated and spontaneous radiation's coherence, Resonators Ruby, and other laser. Material processing with shaping |
CO1, CO2, CO3 |
|
9. |
Modern physics: Relativity, Michelson-Morley experiment, Lorenz-Einstein transformation, Mass energy relation, Quantum effect, Photoelectric effect, Compton Effect; |
CO1, CO2, CO3 |
|
10. |
Atomic Physics: De-Broglie wave, correspondence principles, uncertainty principle, The Rutherford-Bohr model of the atom, Energy levels and spectra, |
CO1, CO2, CO3 |
|
11. |
The Zeeman effect, Electron spin, Many electron atoms and the exclusion principle, vector atom model;
|
CO1, CO2, CO3 |
|
12. |
Nuclear Physics: Introduction, Nuclear constituents, Nuclear binding and nuclear structure, Radioactivity, Radioactive decay, Half-life, |
CO1, CO2, CO3 |
|
13. |
Law of successive disintegration, Radioactive equilibrium, The nucleus, Properties of nucleus, Binding energy, Nuclear reactions, Nuclear fission and fusion, nuclear reactors. |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
Text books:
- M. S. Huq, A. K. Rafiqullah, A. K. Roy Concept of Electricity & Magnetism
- Dr. Giasuddin Ahmed Physics for Engineers part 2
- Kailash K. Sharma Optics: Principles and Applications
- S. N. Ghoshal Nuclear Physics
References:
- K. K. Tewari Electricity and Magnetism with Electronics
- D. N. Vasudeva Fundamentals of Magnetism and Electricity
- Francis A. Jenkins and Harvey E. White Fundamentals of Optics
- Floyd Karker Richtmyer, Earle Hesse Kennard, John N. Cooper Introduction to Modern Physics
- Irving Kaplan Nuclear Physics
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C1 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
Course Title: General English
Course Code: ENG 101
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Language | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course aims to introduce the basic grammar of English language.
Course Objectives:
The objectives of this course are:
- To focus on the basics of English grammar for developing integrated language skills.
- To develop the students’ habit of thinking logically and clearly.
- To provide basic grammar rules and involve students into extensive practice.
- To make learners competent in English by the accurate use of grammar.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Discuss (C2, A2) the properties of spoken English (speaking and listening skills) and written English (reading and writing skills). |
|
CO2 |
Discuss (C2, A2) the factors how grammar and vocabulary choices together create a range of different meanings in speech and writing. |
|
CO3 |
Outline (C3, A2) the different ways in which grammar has been described. |
Mapping of Course Outcomes to Program Outcomes:
|
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
C O1 |
|
|
|
|
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||
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C O2 |
|
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||
|
C O3 |
|
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|
|
|
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Sounds and Pronunciation: English sounds and pronunciation development |
CO1 |
|
2. |
Grammar and Vocabulary: Content related words and expressions and how to apply them in written texts |
CO2 |
|
3. |
Tense and types, Parts of Speech: Noun, pronoun, adjective, adverb, verb, Preposition and article, Conditionals |
CO3 |
|
4. |
Phrasal Verb |
CO2 |
|
5. |
Wh/yes-no questions |
CO3 |
Text Books : (for grammar purpose)
Author Book Name
- Raymond Murphy Intermediate English Grammar
- John Eastwood Oxford English Grammar
- Cliff’s TOEFL - a handbook
- P.K. Dey Sarkar A textbook Higher English Grammar
- R. A. Close The English We Use
- W. Stannard Allen Living English Structure
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO10 |
C2, A2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1, PO10 |
C2, A2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1, PO10 |
C3, A2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final Exam |
Course Title: Developing English Skills
Course Code: ENG 103
| Credits: 2 | Class Hours/Week: 2 |
| Course Type: Language | Pre-requisite: GE |
| CIE Marks: 100% | SEE Marks: |
Course Rationale:
This is an advanced course for students to learn reading, writing, listening and speaking skills.
Course Objectives:
The objectives of this course are to:
- Develop a student's writing skill, listening skill.
- Improve the ability to note taking.
- Grow students speaking English through group discussion.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
D Demonstrate (C2) and practice (A2) English listening and speaking effectively. |
|
CO2 |
Demonstrate (C2) and practice (A2) English writing and reading skills. |
|
CO3 |
Communicate (C3) and work (A2) collaboratively with others. |
Mapping of Course Outcomes to Program Outcomes:
|
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
C O1 |
|
|
|
|
|
|
|
|
|
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|
C O2 |
|
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|
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|
|
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|
C O3 |
|
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|
|
|
|
|
|
|
|
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Developing Writing Skill: Letter Writing: formal and informal, Report writing; Business communication and tenders, business letters, letters of opinion, application and CV writing, e-mail, memo, etc.
|
CO1 |
|
2. |
Listening Skill and Note Taking: Listening to recorded texts and class lectures and learning to take useful notes based on listening. |
CO2 |
|
3. |
Developing Speaking Skill: Oral skills including communicative expressions for personal identification, life at home, giving advice and opinion, instruction and directions, requests, complaints, apologies, describing people and places, narrating events. |
CO3 |
|
4. |
Discussion: A group of students to be brought on the dais at a time. Other students of the class will be interrogating and likewise every student should be brought in turn and questions should be asked from the fields of literature, science, current politics, international affairs, games and sports, etc. The Instructor will act as a conductor.
|
CO3 |
Text Books, Reference Books and Other Resources:
- English Grammar in Use by Raymond Murphy.
- Cambridge English advanced vocabulary
- Cambridge English for IELTS
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2, A2 |
Lecture notes, PPT slides, web content |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1 |
C2, A2 |
Lecture notes, PPT slides, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO9, PO10 |
C3, A2 |
Lecture notes, PPT slides, web content |
Class Test, Assignment, Midterm, Assignment, Final Exam |
Course Title: Technical Writing & Presentation
Course Code: ENG 401
| Credits: 2 | Class Hours/Week: 2 |
| Course Type: Language | Pre-requisite: GE |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
The course aims to equip students with the skills and knowledge necessary to effectively communicate technical information in a clear, concise, and professional manner. In today's highly interconnected and information-driven world, the ability to convey complex technical concepts to various audiences is crucial in fields such as engineering, computer science, business, and science.
Course Objectives:
The objectives of this course are:
- To develop the skills necessary to communicate technical information clearly, concisely, and accurately to various audiences.
- To develop skills in collaboration, communication, and negotiation to produce cohesive and unified documents and presentations.
- To acquire skills in designing and delivering effective visual presentations using tools like PowerPoint or other presentation software.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Use (C3) and select (A2 ) appropriate words to make sentence and then paragraph, reports etc. |
|
CO2 |
Use ( C3 ) and practice ( A2 ) modern tools to prepare technical and scientific documents. |
|
CO3 |
Use ( C3) and explain (A4 ) information effectively. |
Mapping of Course Outcomes to Program Outcomes:
|
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
C O1 |
|
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√ |
√ |
|
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|
C O2 |
|
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|
√ |
|
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|
√ |
√ |
|
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|
C O3 |
|
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|
|
|
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|
√ |
√ |
|
|
Course Description:
|
SL. No. |
Course Content |
COs |
|
1. |
Beginning to Write: a) Making sensible sentences. b) Joining and expanding sentences. c) Contracting sentences. d) Logical development of sentences in context using an idea. e) Clear and effective communication of information. |
CO1, CO2, CO3 |
|
2. |
Reading for Writing: Students will be required to comprehend modern prose-passages drawn from different disciplines with attention to their (a) context, (b) vocabulary, and (c) syntax, and deliver feedback in the form of précis, summaries, and comprehension answers. They will also be required to present their writings before the class for discussion and reactions by the peers. |
CO1, CO2, CO3 |
|
3. |
Expanding Writing: a) Writing paragraphs on technical aspects. b) Writing short, free and guided compositions. c) Developing essays on technical issues. d) Writing reports, memos and business letters. e) Editing compositions for clarity and effectiveness. |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
- Engineer’s Guide to Technical Writing by Kenneth G. Budinski
- Thinking on Paper by J.H. Barton and V.A. Howard
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO9, PO10 |
C3, A2 |
Lectures notes, PPT slides, Audio/Video content, Problem Solving |
Group Work, Class Test, Assignment, Presentation, Viva |
|
CO2 |
PO5, PO9, PO10 |
C3, A2 |
Lectures notes, PPT slides, Audio/Video content, Editing Software, Problem Solving |
Group Work, Class Test, Assignment, Presentation, Viva |
|
CO3 |
PO9, PO10 |
C3, A4 |
Lectures notes, PPT slides, Audio/Video content, Problem Solving |
Group Work, Class Test, Assignment, Presentation, Viva |
Course Title: Engineering Mathematics I
Course Code: MAT 105
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Mathematics | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
It is essential for the engineering/science students to develop strong analytic skills which cannot be achieved without learning calculus of one and multiple variables. This course is intended to build up strong base in calculus as well as to include the experience of applications of its contents in the relevant courses of science/engineering.
Course Objectives:
The objectives of this course are:
- To enhance the understanding and problem-solving skills on related/necessary basic mathematical topics required for learning ordinary and partial differentiation.
- To develop the basic concepts of differentiation in its wide scope.
- To build up problem solving experience in each relevant calculus topic along with addition of application familiarity in the related areas of science/engineering.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Explain (C2) different ways of representing functions: graphical, numerical, analytical or verbal and understand the connection among these representations. |
|
CO2 |
Use (C3) derivatives to solve a variety of problems. |
|
CO3 |
Illustrate (C3) series expansion of functions and apply series concept in engineering problems. |
|
CO4 |
Calculate (C3) geometric properties and relationships to solve multistep problems in two dimensions. |
Mapping of Course Outcomes to Program Outcomes:
|
COs |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
CO1 |
√ |
√ |
|
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|
|
|
|
|
|
|
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|
CO2 |
√ |
√ |
|
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|
|
|
|
|
CO3 |
√ |
√ |
|
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|
|
|
|
|
|
CO4 |
√ |
√ |
|
|
|
|
|
|
|
|
|
|
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Function, Various types of functions, Domain and range of the function, Graphical representation of function, Limit of function, Continuity of function |
CO1 |
|
2. |
Differentiability of function |
CO1, CO2 |
|
3. |
Differential co-efficient of various types of functions |
CO2 |
|
4. |
Successive Differentiation |
CO2, CO3 |
|
5. |
Leibnitz Theorem, Exercises on Leibnitz Theorem |
CO1, CO2, CO3 |
|
7. |
Roll’s Theorem and exercises, Mean value theorem and exercises |
CO1 |
|
8. |
Expansion of functions |
CO3 |
|
9. |
Euler’s Theorem |
CO2 |
|
10. |
Partial Differentiation |
CO3 |
|
11. |
Transformation of co-ordinate axes, Pair of straight lines, equations of conics and reduction to standard forms, Tangent, Normal, Asymptote, Second degree equation |
CO4 |
Text Books, Reference Books and Other Resources:
- Calculus—A New Horizon: By Howard Anton
- The Elements of Coordinate Geometry: by S. L. Loney
- Calculus & Analytic Geometry: by George B Thomas, Jr.
- The Analytical Geometry of the Conic Sections: by The Rev. E. H. Askwith
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture, Notes, Problem solution |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
|
CO4 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
Course Title: Engineering Mathematics II
Course Code: MAT 107
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Mathematics | Pre-requisite: EM I |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course aims to build up basics in integral calculus & linear differential equations in the context of engineering applications.
Course Objectives:
The objectives of this course are:
- To help the students to determine length, area & volumes using integration.
- To develop the ability to solve the differential equations in the context of engineering problems.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Determine (C2) indefinite and definite integral of algebraic, exponential, logarithmic, inverse functions. |
|
CO2 |
Apply (C3) integration to calculate Arc, Areas of regions in a plane, Volumes of solids, surface area of solid revolution. |
|
CO3 |
Identify (C2) order and degree of the differential equation. Distinguish between linear, non- linear, homogenous and Exact differential equation also solve 1 st order and 1 st degree differential equation.
|
Mapping of Course Outcomes to Program Outcomes:
|
COs |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
CO1 |
√ |
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CO2 |
√ |
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CO3 |
√ |
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Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Integration of various types of functions, Substitution method, Integration by Parts, Properties of definite integral, Beta and Gamma function
|
CO1 |
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2. |
Integration of various types of functions, Substitution method Integration by Parts, Properties of definite integral, Beta and Gamma function, Rectification, Area of a surface, Volume of solids of revolution |
CO2 |
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3. . |
Integration of various types of functions, Substitution method, Integration by Parts, Properties of definite integral, Beta and Gamma function, Rectification Area of a surface, Volume of solids of revolution, Order and Degree of differential equation, Variable separable, Homogenous differential equation, Linear differential equation Exact differential equation solution of linear differential equations with constant coefficients series solution of differential equations
|
CO3 |
Text Books, Reference Books and Other Resources:
- Calculus & Analytic Geometry: by George B Thomas, Jr.
- Differential Equations: by Erinu Kresgige
- Advanced Engineering Mathematics: by Peter V. O’Neil
- An Introduction to Differential Equation and Tensor Analysis: by Syed Md. Farid
Ordinary and Partial Differential Equations: by M D. Raisinghania
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Notes, Problem solution |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO2 |
PO1 |
C3 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO3 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Midterm Exam, Final Exam |
Course Title: Engineering Mathematics III
Course Code: MAT 201
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Mathematics | Pre-requisite: EM II |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is intended to build up strong bases in the complex number system and its relevant calculus, in vector calculus, and in statistics and probability, as well as to include the experience of applications of its contents in the relevant courses of science/engineering.
Course Objectives:
The objectives of this course are to:
- Enhance and broaden the contents covered in pre-requisite math courses, and builds up a moderately strong base in statistics and probability.
- This course also highlights the basic concept of vector calculus and Statistics (Probability, Distribution, Sampling, etc.).
- While doing the above it builds up problem solving experience in each relevant topic along with the addition of application familiarity in the related areas of science/engineering.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2) complex analysis techniques for geometric interpretation. |
|
CO2 |
Calculate (C3) vector field parameters using vector integration. |
|
CO3 |
Comprehend (C2) the formulation of statistical data from various distributions. |
|
CO4 |
Analyze (C4) real-world problems using various probability models. |
Mapping of Course Outcomes to Program Outcomes:
|
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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C O1 |
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C O2 |
√ |
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C O3 |
√ |
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CO4 |
√ |
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Course Description:
|
SL No. |
Course Content |
COs |
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1. |
Complex Number System, Analytic Function, Harmonic Function Cauchy-Riemann theorem, function, exercise Construction of analytic functions, Cauchy’s theorem, Cauchy’s Integral formula, exercises Cauchy’s Residue theorem, Exercises on Series Theorem.
|
CO1 |
|
2. |
Vector Differentiation, Del operator, gradient, divergence, curl, Laplacian operator, Line, Surface and Volume integral, Exercises, Gauss’s Theorem, exercises, Green’s Theorem, exercises, Stoke’s theorem, exercises |
CO2 |
|
3. |
Basic concepts of frequency distribution, Measures of location and variation Permutation, Combination
|
CO3 |
|
4. |
Probability Distribution, Binomial, Poisson’s Distribution
|
CO4 |
T e xt Books, Reference Books and Other Resources:
- A Text Book on Co-ordinate Geometry with Vector Analysis: By A. F. M. Abdur Rahman and P. K. Bhattacharjee
- Advanced Engineering Mathematics: by Peter V. O’Neil
- Basic Statistics & Probability: by S. K. Gupta
- An Introduction to Statistics and Probability: by M. Nurul Islam
- Theory and Problems of Complex Variables: by Murray R. Spiegel
M apping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Problem solution |
Assignment, Class Test, Mid Term, Final |
|
CO2 |
PO1 |
C3 |
Lecture notes, Problem solution |
Assignment, Class Test, Mid Term, Final |
|
CO3 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final |
|
CO4 |
PO1 |
C4 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final |
Course Title: Engineering Mathematics IV
Course Code: MAT 203
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Mathematics | Pre-requisite: EM III |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
It is essential for the engineering/science students to develop strong analytic skills which cannot be achieved without extending knowledge and skills obtained in the mathematics courses (MAT 105, MAT 107, MAT 201) and without including matrix methods in particular and Linear Algebra in general. This course is intended to build up strong bases of Laplace transforms, Fourier analysis, partial differential equations (P. D. E.), matrix, and Linear Algebra, as well as to include the experience of applications of its contents in the relevant courses of science/engineering.
Course Objectives:
The objectives of this course are to:
- This course enhances and broadens the contents covered in MAT 105, MAT 107, & MAT 201.
- Toward the above goal, it develops the basic concepts of Laplace transforms, Fourier analysis, matrix, and Linear Algebra in their wide scopes, and of P. D. E in its relevant scopes.
- While doing the above it builds up problem solving experience in each relevant topic along with the addition of application familiarity in the related areas of science/engineering. Etc.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Apply (C3) different types of matrices and determinants in solving real time engineering problems. |
|
CO2 |
Solve (C3) different types of matrix and linear transformation. |
|
CO3 |
Apply (C3) Fourier analysis to convert time domain signal to frequency domain signal and vice-versa. |
|
CO4 |
Solve (C3) basic properties, inverse properties, differential and integral equations using Laplace Transformation. |
Mapping of Course Outcomes to Program Outcomes:
|
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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C O1 |
√ |
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C O2 |
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C O3 |
√ |
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CO4 |
√ |
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Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Basic definition of matrix, Inverse and Rank of a matrix Test of solution system, State and prove Cayley-Hamilton theorem & verify some matrix |
CO1 |
|
2. |
Eigen values and Eigen vectors, Applications of Eigenvalues and Eigenvectors, Geometrical meaning of Linear Independence and discussion on CT answer script, Application, Vector Space and Subspace, Linear combination, Application
|
CO2 |
|
3. |
Formulation of Fourier series, Formulation of Fourier series, Some example of Fourier series with graph, Review
|
CO3 |
|
4. |
Some important properties of Laplace transformation and calculate problems, Established basic formula of Laplace transformation in different function, Some important properties of Laplace transformation and calculate problems, Laplace transform of first derivative to n th derivatives, Definition of inverse Laplace transform and calculate problems, Solution of initial value problem by Laplace transform, solution of integral equation by Laplace transform Application
|
CO4 |
Text Books, Reference Books and Other Resources:
- Linear Algebra By Howard Anton
- Mathematical Physics By B.D.Gupta
- Linear Algebra by Abdur Rahman
- Linear Algebra & Its Applications by David C. Lay
- Advanced Engineering Mathematics by Peter V. O’Neil
- Fourier Series and Boundary Value Problems by Charchil
- Laplace Transform by M. R. Spigel
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Lecture, Notes, Problem solution |
Class Test, Midterm, Assignment, Final |
|
CO2 |
PO1 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Midterm, Assignment, Final |
|
CO3 |
PO1 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Midterm, Assignment, Final |
|
CO4 |
PO1 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Midterm, Assignment, Final |
Course Title: Introduction to Computer Systems Laboratory
Course Code: CSE 110
| Credits: 2 | Class Hours/Week: 4 |
| Course Type: Core | Pre-requisite: |
| CIE Marks: 40 | SEE Marks: 60 |
Course Rationale:
This course is to introduce the basic computer system and computer programming principles.
Course Objectives:
The objectives of this course are:
- To introduce the fundamentals of computer systems.
- To help students hands-on use of: Word processing, Spreadsheet, and Presentation applications.
- To familiarize with number systems.
- To introduce basic programming language.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Define (C1) the fundamental concepts of a computer system and number systems. |
|
CO2 |
Use (C3) word processing, spreadsheet, and ppt presentation for solving engineering tasks. |
|
CO3 |
Execute (C3) basic computer programming principles like data types, programming constructs, input and output operations. |
|
CO4 |
Report (A3) lab results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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|
CO2 |
√ |
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CO3 |
√ |
√ |
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|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Generation of Computer, Functions of the Different Computer Units, Input & Output Devices, Computer Memories and Software. |
CO1, CO4 |
|
2. |
Number Systems: Binary, Octal, Decimal and Hexadecimal. |
CO1, CO4 |
|
3. |
Office applications: MS Word, MS Excel, MS Power Point |
CO2, CO4 |
|
4. |
Introduction to C Language: Flow Charts, Identifiers, Data Types, Variables, Constants, Input/output Statements, Operators and Expressions, Conditional Statements (If, else, switch, etc.), Looping statements (for, while, do-while), arrays. Flow Charts, Arithmetic Operators and Expressions: Evaluating Expressions, Precedence and Associativity of Operators, Type Conversions. Flow Charts, Conditional Control Statements: Bitwise Operators, Relational and Logical Operators. Flow Charts, Conditional Control Statements: If, else If. Flow Charts, Conditional Control Statements: Switch Statement and Examples. Flow Charts, Looping Statements: For, While and Do-While Statements with Examples.
|
CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Introduction to computers ---- (Peter Norton)
- C- The Complete Reference ---- (Herbert Schildt)
- Schaum's Outline of Programming with C ---- (Byron S. Gottfried)
- Programming in ANCI C ---- (E. Balagurusami)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C1 |
Lecture notes, PPT slides, problem solving, web content |
Lab Performance |
|
CO2 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Lab Performance |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Lab Performance, Lab Exam |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
Course Title: Electrical Circuit I
Course Code: EEE 101
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Core | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is intended to enable the students to learn the fundamentals of electrical circuits. Use the acquired knowledge to understand the working and operations of electrical circuits to solve the problems for industrial opportunities.
Course Objectives:
The objectives of this course are:
- To provide the knowledge of Direct Current (DC) and Alternating Current (AC) Circuits.
- Helping the students to develop the ability to solve the unknown electrical parameters which are used to design electrical circuits.
- To develop skills to analyze the behavior of electrical circuits.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Demonstrate (C3) the electrical parameters which are used to design electrical and electronic devices. |
|
CO2 |
Illustrate (C3) the circuit laws, network analysis and methodologies to solve DC as well as AC circuits/networks. |
|
CO3 |
Solve (C3) different types of circuit theorems to find the unknown parameters of an electrical circuit/network. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
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CO1 |
√ |
√ |
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CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Circuit Theorems: Fundamental electrical concepts, Electrical parameters in AC and DC circuits, Measuring devices in the electrical system, Different types of materials, Temperature effect on materials, Ohm’s Law, KVL, KCL, VDR, CDR. |
CO1, CO2 |
|
2. |
DC Circuits (DC): Series DC circuits, Parallel DC Circuits, Series-parallel circuits. |
CO1, CO2 |
|
3. |
Method of Analysis and Theorems: Different types of circuit conversions, Branch Current analysis, Mesh analysis, Nodal analysis, Network theorems. |
CO2, CO3 |
|
4. |
AC Circuits (AC): The Basic Elements and Phasors: R branch, L branch, C branch, and RLC branch Series AC circuits, Parallel AC circuits, Series-parallel AC circuits. Reasoning Circuit: Series and Parallel circuits. |
CO1, CO2 |
Text Books, Reference Books and Other Resources:
- Fundamentals of Electric Circuits, Charles K. Alexander & Matthew N. O. Sadiku
- Introductory Circuit Analysis, Robert L. Boylestad
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Electrical Circuit I Laboratory |
|
Course Code: EEE 102 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This course is intended to enable the learners to analyze the behavior of electrical circuits, use the acquired knowledge to implement or design efficient electrical circuits practically to solve real world problems.
Course Objectives:
The objective of the course is to enable the students to
- To provide practical knowledge of the electrical circuits as well as the technical skills to implement such electrical circuits.
- To help the students to pursue further studies in electrical or telecommunications engineering as well as some other related engineering disciplines including computer engineering.
- This course covers practical works that will be helpful for students to build and analyze devices in real world.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Execute (C3) the circuit network and theorems related to DC and AC circuits/networks. |
|
CO2 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
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CO1 |
√ |
√ |
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|
CO2 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1 |
Laboratory work based on theory course EEE 1101: Introduction to Electrical Engineering |
CO1, CO2 |
Text and Reference books:
- Electrical Circuit Lab Manual Book
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO2 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Mechanical Engineering Drawing & CAD Laboratory |
|
Course Code: ME 102 |
|
Credits: 1 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
This course leads students to an understanding of engineering drawing, an essential means of communication in engineering.
Course Objectives:
The main objectives of this course are:
- Familiarization and use with drawing instruments and conventions in making engineering drawings.
- Freehand single view and multi-view sketching.
- Isometric sketching techniques and multi-view projections.
- Tolerance and dimensioning and applying them in drawing exercises.
- Use of AutoCAD (Or Solid Works) in making engineering drawings with dimensions and taking sectional views.
- Drawing, manipulation and modification of solids using AutoCAD (Or Solid Works) Extraction of multiple views from a solid model in AutoCAD (Or Solid Works).
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Use (C3) drawing instruments in making an engineering drawing. |
|
CO2 |
Describe (C2) different types of lines, drawing paper sizes, and grades of pencils. |
|
CO3 |
Illustrate (C3) freehand single view, multi-view sketches, and isometric sketches. |
|
CO4 |
Use (C3) AutoCAD (Or Solid Works) to draw plane drawing. |
|
CO5 |
Demonstrate (C3) multi view projections using AutoCAD (Or Solid Works). |
|
CO6 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
√ |
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CO2 |
√ |
√ |
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|
CO3 |
√ |
√ |
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CO4 |
√ |
√ |
√ |
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|
CO5 |
√ |
√ |
√ |
|||||||||
|
CO6 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
This course contributes towards the engineering topics component of the mechanical engineering curriculum by familiarizing students with the state-of-the-art CAD and FEA software for modeling, analyzing and designing mechanical components. This course brings into focus the Introduction, Orthographic drawings, First and third angle projections, scale drawing, sectional view, isometric views, missing line, auxiliary view, detail and assembly drawing, project on engineering drawing and CAD using AutoCAD or contemporary packages instructed by the teachers. The students also understand the requirements for good engineering drawings, and are able to apply these to their work/projects. |
CO1, CO2, CO3, CO4, CO5, CO6 |
Text Books, Reference Books and Other Resources:
- AutoCAD – 2002 instant reference, by Goerge Omura & B. Robert Colloria.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C3 |
Demonstration, PPT slides |
Lab performance, Quiz, Lab Exam |
|
CO2 |
PO1, PO2 |
C2 |
Demonstration, PPT slides |
Lab performance, Quiz, Lab Exam |
|
CO3 |
PO1, PO2 |
C3 |
Demonstration, PPT slides |
Lab performance, Quiz, Lab Exam, |
|
CO4 |
PO1, PO2, PO5 |
C3 |
Demonstration, PPT slides |
Lab performance, Quiz, Lab Exam, |
|
CO5 |
PO1, PO2, PO5 |
C3 |
Demonstration, PPT slides |
Lab performance, Quiz, Lab Exam, |
|
CO6 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Discrete Mathematics |
|
Course Code: CSE 103 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course will introduce the basic elements of discrete mathematics for an understanding of
algorithms and data structures used in computing.
Course Objectives:
The main objectives of this course are:
- To acquaint students with a good understanding of the concepts and methods of discrete mathematics
- Helping the students to develop ability in evaluating elementary mathematical arguments and analyzing reasons.
- To help the students to apply appropriate mathematical concepts and operations to interpret data in problem solving.
- To Foster the students to enhance logical thinking for demonstrating the basic algorithms.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C3) a solid understanding of fundamental concepts in discrete mathematics. |
|
CO2 |
Prove (C2) elementary properties of modular arithmetic and explain their applications in computer science. |
|
CO3 |
Apply (C3) graph theory models of data structures and state machines to solve problems of connectivity and constraint satisfaction. |
|
CO4 |
Comprehend (C2) basic concepts in formal language and computability. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
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CO1 |
√ |
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|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Graph theory problem and applications |
CO3 |
|
2. |
Basic number theory and modular arithmetic |
CO2 |
|
3. |
Propositional and Predicate Logic |
CO4 |
|
4. |
Method of Proofs |
CO1 |
Text Books, Reference Books and Other Resources:
- Discrete Mathematics and Its Applications, Seventh Edition by Kenneith H. Rosen
- Discrete Mathematics, Seventh Edition by Richard Johnson
Mapping Course Outcomes with the Teaching – Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Lecture, Problem solution, Web link, PPT slides |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO2 |
PO2 |
C2 |
Lecture, Problem solution, Web link, PPT slides |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO3 |
PO2, PO3 |
C3 |
Lecture, Problem solution, PPT slides, Web link |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO4 |
PO1 |
C2 |
Lecture, Problem solution, PPT slides Web link |
Assignment, Class Test, Midterm Exam, Final Exam |
|
Course Title: Structured Programming |
|
Course Code: CSE 111 |
|
Credits: 2 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course introduces computer programming and problem solving in a structured program logic environment.
Course Objectives:
The objectives of this course are:
- To introduce the student with fundamental principles, typical characteristics and mechanism of structured programming.
- To introduce students with the algorithmic way of thinking and problem solving by computers.
- To help the student to enhance their analysing skills and use the same for writing program in C.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Comprehend (C2) the fundamental concepts of structured programming such as variables, data types, operators, and control statements. |
|
CO2 |
Apply (C3) fundamental programming constructs such as control structures, functions, dynamic memory allocation, file management to solve programming problems. |
|
CO3 |
Develop (C3) modular and reusable code by implementing user-defined functions and data types. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Basic overview of C tokens, Variable, Variable declaration, Operators, input / output, opening and closing a file, creating a file, processing a file. |
CO1 |
|
2. |
Control Statement: Decision Making and Branching (if-else, nested if-else, switch-case, goto) |
CO2 |
|
3. |
Control Statement: Looping (for, while, do-while, nested looping), break and continue statement |
CO2 |
|
4. |
One-dimensional Array, Multidimensional array, String, Array of Strings, user defined function, recursion function, pointers, structure & union.
|
CO2, CO3 |
Text Books, Reference Books and Other Resources:
- Programming in ANSI C. (Latest Edition) ---- (E. Balagurusamy)
- Teach Yourself C –-- (Herbert Schild)
- Programming with C ---- (Schaum’s Outlines)
- The C Programming Language ---- (C Kernighan & D.M. Ritchie)
- Theory and Problems of Programming with C ---- (Byron S. Gottfried)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture notes, PPT slides, problem solving |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO3 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving |
Assignment, Class Test, Midterm Exam, Final Exam |
|
Course Title: Structured Programming Laboratory |
|
Course Code: CSE 112 |
|
Credits: 2 Class Hours/Week: 4 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
Intended to familiarize with various techniques of programming aimed at developing the skills of analyzing and solving problems by using functions/methods, block structures, control statements, file etc.
Course Objectives:
The objectives of this course are:
- To introduce the student's various concepts and structures for writing programs.
- To evaluate the opportunities to develop basic programming skills with respect to program design and development.
- To develop logical and analytical ability through problem solving.
- To make the students interested in Competitive Programming.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2) a sound understanding of fundamental programming concepts, including variables, data types, control structures, functions, and arrays. |
|
CO2 |
Apply (C3) different types of structured programming tools to solve real world problems. |
|
CO3 |
Debug (C3) structured programs to identify and correct errors. |
|
CO4 |
Analyze (C4) codes to improve readability, maintainability, and efficiency. |
|
CO5 |
Describe (A3) the importance of Competitive Programming like IUPC, NCPC, ICPC etc. |
|
CO6 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
|||||||||||
|
CO5 |
√ |
√ |
||||||||||
|
CO6 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Compiler/IDE setup, Basic input/output, file-handling, C program without using conditional and loop statements |
CO1, CO6 |
|
2. |
Problem solving using Control Structures and loops (if-else, nested if-else, switch-case, for loop, nested for loops, while loops, do-while loops), one dimensional array and multi-dimensional array, string processing, user defined functions, structure and unions. |
CO1, CO2, CO6 |
|
3. |
Where Do Errors Come from in Coding? Common programming errors and how to handle them. Error handling, Debugging and Testing |
CO3, CO6 |
|
4. |
Reusability, Maintainability, Scalability and performance |
CO4, CO6 |
|
5. |
Introduction to competitive programming (NCPC, ICPC, Online Judge, Contest criteria etc.), problem solving in different online platforms. |
CO5, CO6 |
Text Books, Reference Books and Other Resources:
- Online references
- Programming in ANSI C. (Latest edition) ---- (E. Balagurusamy)
- Schaum's Outline of Programming with C (Schaum's Outline Series) ---- (Byron Gottfried, Latest Edition)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Demonstration, Discussion, Experiment |
Lab Performance, Lab Exam, Quiz |
|
CO2 |
PO1, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Lab Performance, Lab Exam, Quiz |
|
CO3 |
PO5 |
C3 |
Demonstration, Discussion, Experiment |
Lab Performance, Lab Exam, Quiz |
|
CO4 |
PO2 |
C4 |
Demonstration, Discussion, Experiment |
Lab Performance, Lab Exam, Quiz |
|
CO5 |
PO1, PO12 |
A3 |
Demonstration |
Programming Contest Problem Solving |
|
CO6 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Electronics I |
|
Course Code: EEE 211 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ECKT I |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course is focused on beginners to provide foundation knowledge of electronics devices that are used in modern day electronic system.
Course Objectives:
The objectives of this course are -
- To understand the basic knowledge of electronics and devices.
- To provide foundation knowledge to solve unknown parameters of electronic circuits
- and devices.
- To develop skills to design electronic circuits/networks.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Explain (C2) the knowledge about electronic devices and parameters. |
|
CO2 |
Interpret (C2) of electronics parameters that are used to design electronics devices. |
|
CO3 |
Apply (C3) the problems related to electronic systems and designs. |
|
CO4 |
Illustrates (C3) electronics-related circuitry and its interfacing. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
P-N junction as a circuit element: Intrinsic and extrinsic semiconductors, operational principle of p-n junction, contact potential, current-voltage characteristics of a diode, simplified dc and ac diode models, dynamic resistance and capacitance. |
CO1, CO2, CO3 |
|
2. |
Diode circuits: Half wave and full wave rectifiers, rectifiers with filter capacitor, characteristics of a zener diode, zener shunt regulator, clamping and clipping circuits. |
CO1-CO4 |
|
3. |
Bipolar junction transistor: Current components, BJT characteristics and regions of operation, BJT as an amplifier, biasing the BJT for discrete circuits, small signal equivalent circuit models, BJT as a switch. Single stage mid-band frequency BJT amplifier circuits and different type of biasing techniques. Voltage and current gain, input and output impedance of common base, common emitter and common collector amplifier circuits. |
CO1, CO2, CO4 |
|
4. |
Metal-oxide-semiconductor field-effect-transistor (MOSFET): Structure and physical operation of an enhancement MOSFET, threshold voltage, Body effect, current- voltage characteristics of an enhancement MOSFET biasing discrete and integrated MOS amplifier circuits, Current Mirror: Simple CMOS current mirror, Source degenerated current mirror, high output impedance current mirror, Bipolar current mirror; Single-stage MOS amplifiers, MOSFET as a switch, CMOS inverter.
|
CO1- CO4 |
|
5. |
Junction field-effect-transistor (JFET): Structure and physical operation of JFET, transistor characteristics, pinch-off voltage. Differential and multistage amplifiers, Description of differential amplifiers, small-signal operation, differential and common mode gains, RC coupled mid-band frequency amplifier. |
CO1-CO4 |
|
6. |
Active filters: Basics of Op-Amp, its characteristics, Different types of Op-Amp |
CO1, CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Electronics Devices and Circuit Theory by Robert L. Boylestad & Louis Nashelsky.
- Electronics Devices by Thomas L. Floyd.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Problem solving, PPT slide |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO2 |
PO1 |
C2 |
Lecture, Problem solving, PPT slide |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO3 |
PO1 |
C3 |
Lecture, Problem solving, PPT slide |
Assignment, Class Test, Midterm Exam, Final Exam |
|
CO4 |
PO1 |
C3 |
Lecture, Problem solving, PPT slide |
Assignment, Class Test, Midterm Exam, Final Exam |
|
Course Title: Electronics I Laboratory |
|
Course Code: EEE 212 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ECKTL |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This laboratory course is focused on the practical aspects of the course Electronics I course.
Course Objectives:
The objectives of this course are:
- Familiarize with the different component of electronics system such as diode, transistor
- To provide adequate knowledge on electronic devices.
- To make students learn how to use the measurement equipment for electronics system.
- Test the physical characteristics of different component in lab.
- Develop some practical circuits that describe the basic phenomenon of electronics.
- Provide design concept of complex electronics system.
- Introduce with the design issue of the electronic system.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2, P2) different electronic circuits and power supply as well as the BJT amplifier/JFET amplifier, and their operation. |
|
CO2 |
Conclude (C5) and show (P3) the result from experimental data. |
|
CO3 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Familiarization with the components & devices used in Electronics Lab |
CO1 |
|
2. |
Find out the v-i characteristics of a semiconductor diode under forward & reverse biased condition |
CO1, CO2, CO3 |
|
3. |
Design a Half wave rectifier |
CO1, CO2, CO3 |
|
4. |
Design a Full wave rectifier using center taped transformer. |
CO1, CO2, CO3 |
|
5. |
Design a Full wave bridge rectifier.
|
CO1, CO2, CO3 |
|
6. |
Find out the transistor characteristics curve for common emitter configuration. |
CO1, CO2, CO3 |
|
7. |
Find out the transistor characteristics curve for IB vs VBE. |
CO1, CO2, CO3 |
|
8. |
Find out the transistor characteristics curve for common base configuration. |
CO1, CO2, CO3 |
|
9. |
Single stage Common emitter configured NPN transistor amplifier. |
CO1, CO2, CO3 |
|
10. |
Observation of Common collector configured NPN transistor amplifier |
CO1, CO2, CO3 |
|
11. |
Observation of FET performance |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
Lab Manual
CO Delivery and Assessment:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2, P2 |
Lecture & Laboratory Experiments |
Quiz, Performance Test, Report |
|
CO2 |
PO4 |
C5, P3 |
Lecture & Laboratory Experiments |
Performance Test, Report |
|
CO3 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Object Oriented Programming |
|
Course Code: CSE 211 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To empower the learner to perceive the fundamental knowledge of object-oriented programming paradigm and aimed at developing the skills of analyzing and solving real-world problems.
Course Objectives:
The objectives of this course are to:
- Build an understanding of the object-oriented approach in programming.
- Familiarize the student with the writing of computer programs to solve real-world problems in Java.
- To make students learn and appreciate the importance and merits of proper comments in source code and API documentation.
- Be able to write GUI interfaces for a computer program to interact with users, and to understand the event-based GUI handling principles.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Explain (C2) the fundamental OOP concepts (Classes, Operators, Variables, Keywords, Objects, Methods, Constructors, and Packages). |
|
CO2 |
Illustrate (C3) different object-oriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. |
|
CO3 |
Demonstrate (C3) object-oriented features: exception handling, multi-threading, generics, collection framework, file handling, and GUI. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Basic concepts on object-oriented programming (OOP), benefits and application areas of Object-Oriented Programming, procedural vs. OOP programming, Comparison with OOP and other languages paradigm, and important features of OOP |
CO1 |
|
2. |
Class, objects, and constructor: Introducing classes, objects and constructors (class fundamentals, declaring objects, assigning object reference variables) |
CO1 |
|
3. |
Method basics and method overloading: Introducing Methods, this Keyword, Garbage Collection, the finalize () Method, Overloading Methods, using objects as parameters, returning objects, constructor, and constructor overloading. |
CO1, CO2, |
|
4. |
Inheritance: Method overriding, Inheritance, different types of inheritance |
CO2 |
|
5. |
Miscellaneous class: Understanding Static, Introducing Super, Final, Nested, abstract, wrapper, and Inner class |
CO1, CO2 |
|
6. |
Interface: Basics of interface, class vs. interface, multiple inheritances, defining an interface, dynamic initialization |
CO2 |
|
7. |
Multithreaded Programming: Basics of thread, differences between multithreading and multitasking, the concept of multithreaded programming, and different ways to create a new thread. |
CO3 |
|
8. |
Multithreaded Programming: Implementing the Runnable interface, the life cycle of a thread, deadlock, synchronization, and set thread’s priority. |
CO3 |
|
9. |
Managing Errors and Exceptions: Explain different types of errors, Errors vs. Exceptions, and common Java exceptions with the cause of occurrence. Exception handling mechanism, finally blocks, illustrating the usage of throw and throws, user-defined exception. |
CO3 |
|
10. |
Generics: Basic concepts of generics in Java, advantages and use cases. |
CO3 |
|
11. |
Java Graphics: Enumerate the basic concepts of the Swing package. |
CO3 |
|
12. |
Event Handling and Layout Managers: AWT (Abstract Window Toolkit), Delegation Event Model, Event Listeners, and Sources of Events. Enumerate various types of event classes and listener interfaces. Adapter classes. Basics of the layout manager. Discuss different types of layout managers. |
CO3 |
|
13. |
File Handling (Input/Output): Stream in Java, the hierarchy of java stream classes, and purposes of the various stream functions. Stream Tokenizer, random and sequential access file, basic file-related programs to check the I/O. Basic file-related programs to check the I/O. |
CO3 |
|
14. |
Java Collections Framework: Java Map methods e.g., tree map, hash map. relevant programs. Java collections framework and iterator. relevant programs. List, set, and relevant programs. |
CO3 |
Textbooks, Reference Books and Other Resources:
- Programming with Java A Primer--- (E. Balagurusamy)
- Java the Complete Reference --- (Herbert Schildt)
- Java How to Program--- (Deitel and Deitel)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Object Oriented Programming Laboratory |
|
Course Code: CSE 212 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To empower the learner to perceive the fundamental knowledge of object-oriented programming paradigm and aimed at developing the skills of analyzing and solving real-world problems.
Course Objectives:
The objectives of this course are to:
- Build an understanding of the object-oriented approach in programming.
- Familiarize the student with the writing of computer programs to solve real-world problems in Java.
- To make students learn and appreciate the importance and merits of proper comments in source code and API documentation.
- Be able to write GUI interfaces for a computer program to interact with users, and to understand the event-based GUI handling principles.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C3) the fundamental OOP concepts (Classes, Objects and Packages) using Object Oriented Language. |
|
CO2 |
Implement (C3) different object-oriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. |
|
CO3 |
Implement (C3) object-oriented features: exception handling, multi-threading, generics. |
|
CO4 |
Implement (C3) GUI features to develop lightweight application based on constraints. |
|
CO5 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
|||||||||||
|
CO4 |
✓ |
✓ |
||||||||||
|
CO5 |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Basics of Java programming language, equation solving, conditional statement-related problem solving, and loop |
CO1, CO5 |
|
2. |
Class, objects, and constructor: Programs related to Class, Objects and Constructor |
CO1, CO5 |
|
3. |
Method overloading, Method Overriding, Inheritance, Abstraction, Polymorphism, Encapsulation |
CO2, CO5 |
|
4. |
Multithreaded Programming: Programs related to multithreading, creating a new thread, implementing the Runnable interface, synchronization, and setting the thread’s priority. |
CO3, CO5 |
|
5. |
Managing Errors and Exceptions: Programs related to errors and exceptions, common Java exceptions, exception handling mechanism, and finally block, illustrating the usage of throw and throws, user-defined exception. |
CO3, CO5 |
|
6. |
Applet: HTML and applet program integration, graphics programming with the applet, repaint () method, Swing package, Event Handling and Layout Managers |
CO4, CO5 |
Text Books, Reference Books and Other Resources:
- Programming with Java A Primer--- (E. Balagurusamy)
- Java the Complete Reference --- (Herbert Schildt)
- Java How to Program--- (Deitel and Deitel)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO2 |
PO1, PO2 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO3 |
PO1 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO4 |
PO1, PO2 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO5 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Data Structures |
|
Course Code: CSE 221 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Rationale:
Data structure provides a good understanding for organizing and storing data in a computer
such that it can be stored, retrieved, and updated frequently.
Course Objectives:
The main objectives of this course are to:
- Make the students understand the data structures and their implementations.
- Facilitate necessary knowledge about the importance of data structures in the context of writing efficient programs.
- Develop the ability to implement appropriate data structures in problem solving.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Interpret (C2) the basic concepts of data structures, their types and basic operations. |
|
CO2 |
Summarize (C2) the strength and weaknesses of different data structures. |
|
CO3 |
Use (C3) the appropriate data structures in the context of the solution to any given problem. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
|||||||||||
|
CO3 |
✓ |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Data Structures, Basic Operations, and Performance Measurement. |
CO1 |
|
2. |
Introduction to Array, Search, and Sorting Strings: Pattern Matching Algorithm (Naive and KMP) |
CO1, CO2, CO3 |
|
3. |
Types of Linked List and Basic Operations on Linked List |
CO1, CO2, CO3 |
|
4. |
Basic Operations on Stack and Use of Recursion Types of Queue and Basic Operations on Queue |
CO1, CO2, CO3 |
|
5. |
Types of Trees, Representation of Tree, Binary Search Tree, Balanced Search Tree, Efficient Heap |
CO1, CO2, CO3 |
|
6. |
Graph Representation, Traversing Graph, Topological Sorting, Path Matrix, Warshall Algorithm |
CO1, CO2, CO3 |
|
7. |
Hash Function and its Application. |
CO1, CO2 |
Text Books, Reference Books and Other Resources:
- Seymour Lipschutz, Data Structures, McGraw-Hill, 2014.
- Debasis Samanta, Classic Data Structures, Prentice-Hall of India Private Limited, 2009.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery methods and activities |
Assessment tools |
|
CO1 |
PO1 |
C2 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final |
|
CO2 |
PO2 |
C2 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final Examination |
|
CO3 |
PO1, PO2 |
C3 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final Examination |
|
Course Title: Data Structures Laboratory |
|
Course Code: CSE 222 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 40 SEE Marks: 60 |
Rationale:
To practically implement as well analyze the various data structures and basic algorithm
analysis.
Course Objectives:
The main objectives of this course are to:
- Help the students to understand the analysis and design of linear and non-linear data structures in the context of writing efficient programs.
- Develop the ability in identifying and applying the suitable data structure for the given
real- world problem.
Course Outcomes (COs):
|
CO1 |
Describe (C2) the operations of basic data structures. |
|
CO2 |
Classify (C2) the appropriate data structure to solve specific problems. |
|
CO3 |
Solve (C3) problems or improve existing code using learned data structures. |
|
CO4 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
COs |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
|||||||||||
|
CO3 |
✓ |
|||||||||||
|
CO4 |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Identify and apply the basic operations of data structures: Array, Linked List, Stack, Queue, Tree, Graph. |
CO1, CO4 |
|
2. |
Identify the basic data structures and apply solutions: Bubble Sort, Selection Sort, Insertion Sort, Linear Search, Binary Search, Pattern matching: Naïve, KMP, Binary Search Tree, Heap Tree (Using Priority Queue), Breadth-first Search, Depth-first Search |
CO2, CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Data Structures (Third Edition), by Seymour Lipschutz, Publishers: McGraw-Hill.
- Classic Data Structures, by D. Samanta, Publishers: Prentic-Hall of India Private Limited.
- Data Structures and Algorithms in Python, by Michael T. Goodrich, publisher: VP & PUBLISHER
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO2 |
PO2 |
C2 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO3 |
PO2 |
C3 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Digital Electronics |
|
Course Code: EEE 311 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course aims to empower the learner to inspect and perceive the fundamental knowledge of digital electronics and develop sufficient background for advanced digital electronic courses.
Course Objectives:
The objectives of this course are to:
- Provide a modern introduction to logic design and the basic building blocks used in technical areas in particular digital computers.
- Familiarize the student with fundamental principles of 21st century’s digital design.
- Provide coverage of classical hardware design for both combinational and sequential logic circuits.
- Develop research skills and aspects of professional practice through group-bases assignments and team works that leads them to become successful self-employed, motivator, entrepreneur and manager.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) the fundamental concepts, theories and techniques used in digital electronics. |
|
CO2 |
Interpret (C2) various combinational and sequential circuits. |
|
CO3 |
Implement (C3) descriptions of logical problems to efficient digital logic circuits. |
|
CO4 |
Demonstrate (C3) memory, interfacing and converter. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Number systems: Representation of numbers in different bases, Addition and subtraction in different bases, complement: Subtraction using complements, Binary multiplication & division. |
CO1 |
|
2. |
Binary codes: Different coding system, Boolean algebra, various gates, Sum of products and product of sums, Standard and canonical forms and other logical operations. |
CO1 |
|
3. |
Simplification of Boolean functions: Karnaugh map method, Tabular method of simplification; Implementation of logic circuit using various gates, Universal gates. |
CO2 |
|
4. |
Combinational logic circuit: Design procedure: Adder, Subtractor, Code converters, Parity bit checker and magnitude comparator, Analysis of different combinational circuits, Encoder, decoder, Multiplexer, Demultiplexer, ROM, PLA and their applications. |
CO3 |
|
5. |
Flip-flops: SR, JK, Master slave, T and D type flip-flops and their characteristic tables & equations; Triggering of flip-flops, Flipflop, Excitation table. |
CO3 |
|
6. |
Sequential circuits: Introduction to sequential circuits, Analysis and synthesis of synchronous and asynchronous sequential circuits. |
CO3 |
|
7. |
Counters: Classifications, Synchronous and asynchronous counter design and analysis, Ring counter, Johnson counters, Ripple counter and counter with parallel load. |
CO3 |
|
8. |
Registers: Classification, Shift registers, Circular registers and their applications and registers with parallel load. Basic Concept of Application Specific IC (ASIC) design. |
CO3 |
|
9. |
Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS and CMOS logic and their characteristics, principles of operation and application. |
CO2 |
|
10. |
Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS and CMOS logic and their characteristics, principles of operation and application. |
CO2 |
|
11. |
Memory Units: Various memory devices and their interfacing. |
CO4 |
|
12. |
Converters: Digital to Analog (D/A), Analog to Digital (A/D) converters, and their applications. |
CO4 |
Text Books, Reference Books and Other Resources:
- Digital Logic and Computer Design by M. Morris Mano
- Modern Digital Electronics, by R.P. Jain.
- Digital Electronics, by Tocci.
- Computer Engineering by M. M. Mano,
- Digital Computer Electronics by A.P. Malvino.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO2 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO3 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO4 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
Course Title: Digital Electronics Laboratory |
|
Course Code: EEE 312 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This subject aims to get acquainted with integrated circuits, to design and implement digital circuits, and to be able to troubleshoot implemented circuits.
Course Objectives:
The objective of the course is to enable the students to:
- Make students understand the operations and applications of various digital electronic circuits.
- Help students develop the analyzing skills of digital electronic circuits.
- Help students develop the ability to present the results of investigations orally and in writing.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C3, P2) different logic gate circuits as well as the multiplexer/demultiplexer and counter operation. |
|
CO2 |
Conclude (C4) and show (P3) the result from experimental data. |
|
CO3 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Familiarization of Digital Electronics Laboratory |
CO1 |
|
2. |
Familiarization of the Digital Logic gates ICs, truth tables & verification of Fundamental logic gates. |
CO1, CO2, CO3 |
|
3. |
Boolean function implementation. |
CO1, CO2, CO3 |
|
4. |
Verification of universality of NAND & NOR gates |
CO1, CO2, CO3 |
|
5. |
Verification of Half adder & Full adder circuit. |
CO1, CO2, CO3 |
|
6. |
Verification of Half subtractor & Full subtractor circuit. |
CO1, CO2, CO3 |
|
7. |
Implementation of 4-Bit Parallel Adder Using 7483 |
CO1, CO2, CO3 |
|
8. |
Verification of basic operation of a Multiplexer and Demultiplexer. |
CO1, CO2, CO3 |
|
9. |
Design and verify the 4-bit Synchronous counter. |
CO1, CO2, CO3 |
|
10. |
Design and verify the 4-bit Asynchronous counter. |
CO1, CO2, CO3 |
|
11. |
Familiarization of different types of flip-flops. |
CO1, CO2, CO3 |
Text and Reference books:
- Digital Logic and Computer Design by M. Morris Mano
- Lab Manual
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery methods and activities |
Assessment tools |
|
CO1 |
PO1 |
C3, P2 |
Demonstration, Discussion, Experiment |
Quiz/Written Exam, Performance, Report |
|
CO2 |
PO2 |
C4, P3 |
Demonstration, Discussion, Experiment |
Quiz/Written Exam, Performance, Report |
|
CO3 |
PO10 |
A3 |
Demonstration, |
Report |
|
Course Title: Algorithm Design and Analysis |
|
Course Code: CSE 225 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: DS |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To practically implement basic algorithms, as well as to analyze the runtime and memory use.
Course Objectives:
The main objectives of this course are:
- General Understanding of Basic Algorithms.
- Developing Programming Skills for Solving Real Time Problem using Algorithm
- Conduct experiments to get a sense of the time and storage (memory) efficiency of the program codes.
- Demonstrate advantages and disadvantages of specific algorithms.
- To make students learn how to use the measurement equipment for electronics system.
- Test the physical characteristics of different component in lab.
- Develop some practical circuits that describe the basic phenomenon of electronics.
- Provide design concept of complex electronics system.
- Introduce with the design issue of the electronic system.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2, P2) different electronic circuits and power supply as well as the BJT amplifier/JFET amplifier, and their operation. |
|
CO2 |
Conclude (C5) and show (P3) the result from experimental data. |
|
CO3 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Familiarization with the components & devices used in Electronics Lab |
CO1 |
|
2. |
Find out the v-i characteristics of a semiconductor diode under forward & reverse biased condition |
CO1, CO2, CO3 |
|
3. |
Design a Half wave rectifier |
CO1, CO2, CO3 |
|
4. |
Design a Full wave rectifier using center taped transformer. |
CO1, CO2, CO3 |
|
5. |
Design a Full wave bridge rectifier.
|
CO1, CO2, CO3 |
|
6. |
Find out the transistor characteristics curve for common emitter configuration. |
CO1, CO2, CO3 |
|
7. |
Find out the transistor characteristics curve for IB vs VBE. |
CO1, CO2, CO3 |
|
8. |
Find out the transistor characteristics curve for common base configuration. |
CO1, CO2, CO3 |
|
9. |
Single stage Common emitter configured NPN transistor amplifier. |
CO1, CO2, CO3 |
|
10. |
Observation of Common collector configured NPN transistor amplifier |
CO1, CO2, CO3 |
|
11. |
Observation of FET performance |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
Lab Manual
CO Delivery and Assessment:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2, P2 |
Lecture & Laboratory Experiments |
Quiz, Performance Test, Report |
|
CO2 |
PO4 |
C5, P3 |
Lecture & Laboratory Experiments |
Performance Test, Report |
|
CO3 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Object Oriented Programming |
|
Course Code: CSE 211 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To empower the learner to perceive the fundamental knowledge of object-oriented programming paradigm and aimed at developing the skills of analyzing and solving real-world problems.
Course Objectives:
The objectives of this course are to:
- Build an understanding of the object-oriented approach in programming.
- Familiarize the student with the writing of computer programs to solve real-world problems in Java.
- To make students learn and appreciate the importance and merits of proper comments in source code and API documentation.
- Be able to write GUI interfaces for a computer program to interact with users, and to understand the event-based GUI handling principles.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Explain (C2) the fundamental OOP concepts (Classes, Operators, Variables, Keywords, Objects, Methods, Constructors, and Packages). |
|
CO2 |
Illustrate (C3) different object-oriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. |
|
CO3 |
Demonstrate (C3) object-oriented features: exception handling, multi-threading, generics, collection framework, file handling, and GUI. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Basic concepts on object-oriented programming (OOP), benefits and application areas of Object-Oriented Programming, procedural vs. OOP programming, Comparison with OOP and other languages paradigm, and important features of OOP |
CO1 |
|
2. |
Class, objects, and constructor: Introducing classes, objects and constructors (class fundamentals, declaring objects, assigning object reference variables) |
CO1 |
|
3. |
Method basics and method overloading: Introducing Methods, this Keyword, Garbage Collection, the finalize () Method, Overloading Methods, using objects as parameters, returning objects, constructor, and constructor overloading. |
CO1, CO2, |
|
4. |
Inheritance: Method overriding, Inheritance, different types of inheritance |
CO2 |
|
5. |
Miscellaneous class: Understanding Static, Introducing Super, Final, Nested, abstract, wrapper, and Inner class |
CO1, CO2 |
|
6. |
Interface: Basics of interface, class vs. interface, multiple inheritances, defining an interface, dynamic initialization |
CO2 |
|
7. |
Multithreaded Programming: Basics of thread, differences between multithreading and multitasking, the concept of multithreaded programming, and different ways to create a new thread. |
CO3 |
|
8. |
Multithreaded Programming: Implementing the Runnable interface, the life cycle of a thread, deadlock, synchronization, and set thread’s priority. |
CO3 |
|
9. |
Managing Errors and Exceptions: Explain different types of errors, Errors vs. Exceptions, and common Java exceptions with the cause of occurrence. Exception handling mechanism, finally blocks, illustrating the usage of throw and throws, user-defined exception. |
CO3 |
|
10. |
Generics: Basic concepts of generics in Java, advantages and use cases. |
CO3 |
|
11. |
Java Graphics: Enumerate the basic concepts of the Swing package. |
CO3 |
|
12. |
Event Handling and Layout Managers: AWT (Abstract Window Toolkit), Delegation Event Model, Event Listeners, and Sources of Events. Enumerate various types of event classes and listener interfaces. Adapter classes. Basics of the layout manager. Discuss different types of layout managers. |
CO3 |
|
13. |
File Handling (Input/Output): Stream in Java, the hierarchy of java stream classes, and purposes of the various stream functions. Stream Tokenizer, random and sequential access file, basic file-related programs to check the I/O. Basic file-related programs to check the I/O. |
CO3 |
|
14. |
Java Collections Framework: Java Map methods e.g., tree map, hash map. relevant programs. Java collections framework and iterator. relevant programs. List, set, and relevant programs. |
CO3 |
Textbooks, Reference Books and Other Resources:
- Programming with Java A Primer--- (E. Balagurusamy)
- Java the Complete Reference --- (Herbert Schildt)
- Java How to Program--- (Deitel and Deitel)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Object Oriented Programming Laboratory |
|
Course Code: CSE 212 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To empower the learner to perceive the fundamental knowledge of object-oriented programming paradigm and aimed at developing the skills of analyzing and solving real-world problems.
Course Objectives:
The objectives of this course are to:
- Build an understanding of the object-oriented approach in programming.
- Familiarize the student with the writing of computer programs to solve real-world problems in Java.
- To make students learn and appreciate the importance and merits of proper comments in source code and API documentation.
- Be able to write GUI interfaces for a computer program to interact with users, and to understand the event-based GUI handling principles.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C3) the fundamental OOP concepts (Classes, Objects and Packages) using Object Oriented Language. |
|
CO2 |
Implement (C3) different object-oriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. |
|
CO3 |
Implement (C3) object-oriented features: exception handling, multi-threading, generics. |
|
CO4 |
Implement (C3) GUI features to develop lightweight application based on constraints. |
|
CO5 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
|||||||||||
|
CO4 |
✓ |
✓ |
||||||||||
|
CO5 |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Basics of Java programming language, equation solving, conditional statement-related problem solving, and loop |
CO1, CO5 |
|
2. |
Class, objects, and constructor: Programs related to Class, Objects and Constructor |
CO1, CO5 |
|
3. |
Method overloading, Method Overriding, Inheritance, Abstraction, Polymorphism, Encapsulation |
CO2, CO5 |
|
4. |
Multithreaded Programming: Programs related to multithreading, creating a new thread, implementing the Runnable interface, synchronization, and setting the thread’s priority. |
CO3, CO5 |
|
5. |
Managing Errors and Exceptions: Programs related to errors and exceptions, common Java exceptions, exception handling mechanism, and finally block, illustrating the usage of throw and throws, user-defined exception. |
CO3, CO5 |
|
6. |
Applet: HTML and applet program integration, graphics programming with the applet, repaint () method, Swing package, Event Handling and Layout Managers |
CO4, CO5 |
Text Books, Reference Books and Other Resources:
- Programming with Java A Primer--- (E. Balagurusamy)
- Java the Complete Reference --- (Herbert Schildt)
- Java How to Program--- (Deitel and Deitel)
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO2 |
PO1, PO2 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO3 |
PO1 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO4 |
PO1, PO2 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO5 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Data Structures |
|
Course Code: CSE 221 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Rationale:
Data structure provides a good understanding for organizing and storing data in a computer
such that it can be stored, retrieved, and updated frequently.
Course Objectives:
The main objectives of this course are to:
- Make the students understand the data structures and their implementations.
- Facilitate necessary knowledge about the importance of data structures in the context
of writing efficient programs.
- Develop the ability to implement appropriate data structures in problem solving.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Interpret (C2) the basic concepts of data structures, their types and basic operations. |
|
CO2 |
Summarize (C2) the strength and weaknesses of different data structures. |
|
CO3 |
Use (C3) the appropriate data structures in the context of the solution to any given problem. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
|||||||||||
|
CO3 |
✓ |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Data Structures, Basic Operations, and Performance Measurement. |
CO1 |
|
2. |
Introduction to Array, Search, and Sorting Strings: Pattern Matching Algorithm (Naive and KMP) |
CO1, CO2, CO3 |
|
3. |
Types of Linked List and Basic Operations on Linked List |
CO1, CO2, CO3 |
|
4. |
Basic Operations on Stack and Use of Recursion Types of Queue and Basic Operations on Queue |
CO1, CO2, CO3 |
|
5. |
Types of Trees, Representation of Tree, Binary Search Tree, Balanced Search Tree, Efficient Heap |
CO1, CO2, CO3 |
|
6. |
Graph Representation, Traversing Graph, Topological Sorting, Path Matrix, Warshall Algorithm |
CO1, CO2, CO3 |
|
7. |
Hash Function and its Application. |
CO1, CO2 |
Text Books, Reference Books and Other Resources:
- Seymour Lipschutz, Data Structures, McGraw-Hill, 2014.
- Debasis Samanta, Classic Data Structures, Prentice-Hall of India Private Limited, 2009.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery methods and activities |
Assessment tools |
|
CO1 |
PO1 |
C2 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final |
|
CO2 |
PO2 |
C2 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final Examination |
|
CO3 |
PO1, PO2 |
C3 |
Lecture, Web link, PPT slide |
Assignment, Class Test, Midterm examination, Final Examination |
|
Course Title: Data Structures Laboratory |
|
Course Code: CSE 222 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 40 SEE Marks: 60 |
Rationale:
To practically implement as well analyze the various data structures and basic algorithm
analysis.
Course Objectives:
The main objectives of this course are to:
- Help the students to understand the analysis and design of linear and non-linear data
structures in the context of writing efficient programs.
- Develop the ability in identifying and applying the suitable data structure for the given
real- world problem.
Course Outcomes (COs):
|
CO1 |
Describe (C2) the operations of basic data structures. |
|
CO2 |
Classify (C2) the appropriate data structure to solve specific problems. |
|
CO3 |
Solve (C3) problems or improve existing code using learned data structures. |
|
CO4 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
COs |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
|||||||||||
|
CO3 |
✓ |
|||||||||||
|
CO4 |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Identify and apply the basic operations of data structures: Array, Linked List, Stack, Queue, Tree, Graph. |
CO1, CO4 |
|
2. |
Identify the basic data structures and apply solutions: Bubble Sort, Selection Sort, Insertion Sort, Linear Search, Binary Search, Pattern matching: Naïve, KMP, Binary Search Tree, Heap Tree (Using Priority Queue), Breadth-first Search, Depth-first Search |
CO2, CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Data Structures (Third Edition), by Seymour Lipschutz, Publishers: McGraw-Hill.
- Classic Data Structures, by D. Samanta, Publishers: Prentic-Hall of India Private Limited.
- Data Structures and Algorithms in Python, by Michael T. Goodrich, publisher: VP & PUBLISHER
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO2 |
PO2 |
C2 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO3 |
PO2 |
C3 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Report, Lab exam |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Digital Electronics |
|
Course Code: EEE 311 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course aims to empower the learner to inspect and perceive the fundamental knowledge of digital electronics and develop sufficient background for advanced digital electronic courses.
Course Objectives:
The objectives of this course are to:
- Provide a modern introduction to logic design and the basic building blocks used in technical areas in particular digital computers.
- Familiarize the student with fundamental principles of 21st century’s digital design.
- Provide coverage of classical hardware design for both combinational and sequential logic circuits.
- Develop research skills and aspects of professional practice through group-bases assignments and team works that leads them to become successful self-employed, motivator, entrepreneur and manager.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) the fundamental concepts, theories and techniques used in digital electronics. |
|
CO2 |
Interpret (C2) various combinational and sequential circuits. |
|
CO3 |
Implement (C3) descriptions of logical problems to efficient digital logic circuits. |
|
CO4 |
Demonstrate (C3) memory, interfacing and converter. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Number systems: Representation of numbers in different bases, Addition and subtraction in different bases, complement: Subtraction using complements, Binary multiplication & division. |
CO1 |
|
2. |
Binary codes: Different coding system, Boolean algebra, various gates, Sum of products and product of sums, Standard and canonical forms and other logical operations. |
CO1 |
|
3. |
Simplification of Boolean functions: Karnaugh map method, Tabular method of simplification; Implementation of logic circuit using various gates, Universal gates. |
CO2 |
|
4. |
Combinational logic circuit: Design procedure: Adder, Subtractor, Code converters, Parity bit checker and magnitude comparator, Analysis of different combinational circuits, Encoder, decoder, Multiplexer, Demultiplexer, ROM, PLA and their applications. |
CO3 |
|
5. |
Flip-flops: SR, JK, Master slave, T and D type flip-flops and their characteristic tables & equations; Triggering of flip-flops, Flipflop, Excitation table. |
CO3 |
|
6. |
Sequential circuits: Introduction to sequential circuits, Analysis and synthesis of synchronous and asynchronous sequential circuits. |
CO3 |
|
7. |
Counters: Classifications, Synchronous and asynchronous counter design and analysis, Ring counter, Johnson counters, Ripple counter and counter with parallel load. |
CO3 |
|
8. |
Registers: Classification, Shift registers, Circular registers and their applications and registers with parallel load. Basic Concept of Application Specific IC (ASIC) design. |
CO3 |
|
9. |
Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS and CMOS logic and their characteristics, principles of operation and application. |
CO2 |
|
10. |
Digital IC logic families: Brief description of TTL, DTL, RTL, ECL, I2L, MOS and CMOS logic and their characteristics, principles of operation and application. |
CO2 |
|
11. |
Memory Units: Various memory devices and their interfacing. |
CO4 |
|
12. |
Converters: Digital to Analog (D/A), Analog to Digital (A/D) converters, and their applications. |
CO4 |
Text Books, Reference Books and Other Resources:
- Digital Logic and Computer Design by M. Morris Mano
- Modern Digital Electronics, by R.P. Jain.
- Digital Electronics, by Tocci.
- Computer Engineering by M. M. Mano,
- Digital Computer Electronics by A.P. Malvino.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO2 |
PO1 |
C2 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO3 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
CO4 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Assignment, Class Test, Mid Term, Final Examination |
|
Course Title: Digital Electronics Laboratory |
|
Course Code: EEE 312 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This subject aims to get acquainted with integrated circuits, to design and implement digital circuits, and to be able to troubleshoot implemented circuits.
Course Objectives:
The objective of the course is to enable the students to:
- Make students understand the operations and applications of various digital electronic circuits.
- Help students develop the analyzing skills of digital electronic circuits.
- Help students develop the ability to present the results of investigations orally and in writing.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C3, P2) different logic gate circuits as well as the multiplexer/demultiplexer and counter operation. |
|
CO2 |
Conclude (C4) and show (P3) the result from experimental data. |
|
CO3 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Familiarization of Digital Electronics Laboratory |
CO1 |
|
2. |
Familiarization of the Digital Logic gates ICs, truth tables & verification of Fundamental logic gates. |
CO1, CO2, CO3 |
|
3. |
Boolean function implementation. |
CO1, CO2, CO3 |
|
4. |
Verification of universality of NAND & NOR gates |
CO1, CO2, CO3 |
|
5. |
Verification of Half adder & Full adder circuit. |
CO1, CO2, CO3 |
|
6. |
Verification of Half subtractor & Full subtractor circuit. |
CO1, CO2, CO3 |
|
7. |
Implementation of 4-Bit Parallel Adder Using 7483 |
CO1, CO2, CO3 |
|
8. |
Verification of basic operation of a Multiplexer and Demultiplexer. |
CO1, CO2, CO3 |
|
9. |
Design and verify the 4-bit Synchronous counter. |
CO1, CO2, CO3 |
|
10. |
Design and verify the 4-bit Asynchronous counter. |
CO1, CO2, CO3 |
|
11. |
Familiarization of different types of flip-flops. |
CO1, CO2, CO3 |
Text and Reference books:
- Digital Logic and Computer Design by M. Morris Mano
- Lab Manual
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery methods and activities |
Assessment tools |
|
CO1 |
PO1 |
C3, P2 |
Demonstration, Discussion, Experiment |
Quiz/Written Exam, Performance, Report |
|
CO2 |
PO2 |
C4, P3 |
Demonstration, Discussion, Experiment |
Quiz/Written Exam, Performance, Report |
|
CO3 |
PO10 |
A3 |
Demonstration, |
Report |
|
Course Title: Algorithm Design and Analysis |
|
Course Code: CSE 225 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: DS |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
To practically implement basic algorithms, as well as to analyze the runtime and memory use.
Course Objectives:
The main objectives of this course are:
- General Understanding of Basic Algorithms.
- Developing Programming Skills for Solving Real Time Problem using Algorithm
- Conduct experiments to get a sense of the time and storage (memory) efficiency of the program codes.
- Demonstrate advantages and disadvantages of specific algorithms.
Course Outcomes:
Upon successful completion of the course the students will be able to:
|
CO1 |
Interpret (C2) the fundamental concepts and design paradigms of algorithms. |
|
CO2 |
Calculate (C2) the time and space complexities of various algorithms. |
|
CO3 |
Implement (C3) efficient algorithms in simple engineering design situations. |
Mapping of Course Outcomes to Program Outcomes
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
|||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Fundamental Algorithm Paradigms: Deterministic and nondeterministic algorithm, Divide and conquer algorithms, Dynamic Programming, Greedy algorithms, Minimum Spanning Tree, Single Source Shortest path algorithms, Incremental Improvement, Backtracking, Assignment Problem, Branch & Bound and Approximation Problem. |
CO1 |
|
2. |
Complexity Analysis and Evaluation: Space and time complexity, Order of growth, Recurrences relations, Amortization, Complexity classes. |
CO2 |
|
3. |
Real time applications and complexity comparison for engineering problems. |
CO3 |
Recommended and Supplementary Books:
- Introduction to Algorithms (Third Edition), by Coreman et, Publishers: McGraw-Hill
- Fundamentals of Computer Algorithms, Sartaj Sahni and Sanguthevar Rajasekaran Ellis Horowitz
Mapping of Course Outcomes with Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Web Content, PPT slide |
Class Test, Assignment, Midterm Exam, Final Examination |
|
CO2 |
PO1, PO2 |
C2 |
Lecture, Web Content, PPT slide |
Class Test, Assignment, Midterm Exam, Final Examination |
|
CO3 |
PO1, PO2 |
C3 |
Lecture, Web Content, PPT slide |
Class Test, Assignment, Midterm Exam, Final Examination |
|
Course Title: Algorithm Design and Analysis Laboratory |
|
Course Code: CSE 226 |
|
Credits: 1 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: DSL |
|
CIE Marks: 40 SEE Marks: 60 |
Rationale:
This course introduces students to the general tools and techniques for analyzing and designing computer algorithms.
Course Objectives:
Upon completion of this course, students will be able to do the following:
- Acquaint students with the major algorithms and data structures.
- Foster the analytical and critical analysis of algorithmic design paradigms and methods.
- Apply the knowledge of asymptotic performance of algorithms.
- To facilitate necessary knowledge about algorithms in common engineering design
situations.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Use (C3) the appropriate algorithms to solve problems belonging to randomized, iterative, recursive, dynamic, greedy, graph, backtracking, branch and bound paradigms. |
|
CO2 |
Argue (C5) the efficiency and correctness of the algorithms in CO1. |
|
CO3 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Analysis, Implementation and Evaluation of Divide & conquer algorithms: Merge sort, Quick sort, Dynamic Programming: 0/1 knapsack, Subset Problem; BFS, DFS, Topological Sorting, Minimum Spanning Tree :Prim’s Algorithm, Krushkal’s Algorithm, Single Source Shortest paths: Bellman-Ford, Dijkstra's algorithm; Backtracking: Hamiltonian Cycle, N Queen's problem, Branch & Bound : Travelling Salesman Problem |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
- Introduction to Algorithms (Third Edition), by Coreman et, Publishers: McGraw-Hill
2 Fundamentals of Computer Algorithms, Sartaj Sahni and Sanguthevar Rajasekaran Ellis Horowitz
- Data Structures and Algorithms in Python, by Michael T. Goodrich, publisher: VP & PUBLISHER
Mapping of Course Outcomes with Teaching -Learning and Assessment Delivery and Assessment:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO2 |
C3 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Lab Exam |
|
CO2 |
PO2 |
C5 |
Lecture, Practical Implementation |
Lab Performance, Quiz, Lab Exam |
|
CO3 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Database Management System |
|
Course Code: CSE 237 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course will cover the principles of relational database management systems, as well as recent advances in database theory and practice.
Course Objectives:
- To make the students understand the different issues involved in the design and implementation of a database system in a modern information sys
- To acquaint students with database modeling techniques/tools of the modern era.
- To learn various techniques for managing a database-oriented syste
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2) key concepts of database management system and its security. |
|
CO2 |
Write (C3) database query to serve user requirements. |
|
CO3 |
Plan (C6) to design various data models minimizing database anomalies. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: database systems, purposes, applications, database architecture, database administrator Relational Model: structure, database schema, keys, schema diagrams, relational query, relational algebra Distributed Database (DDB): centralized vs distributed database, homogenous and heterogenous DDB, major objective, storage technique, deadlock, ACID properties, data structure, data mining and warehousing, indexing and hashing |
CO1 |
|
2. |
Query Language: SQL, basic query structure, set operations, NULL values, aggregate functions, nested subqueries, database modification Intermediate SQL: join, views, transactions, integrity constraints, SQL data types, index in SQL, authorization, Advanced SQL: SQL from application program, function, procedure, trigger |
CO2 |
|
3. |
ER model: different attribute, mapping cardinalities, primary key for entity and relationship, strong and weak entity, redundant attribute, reducing ER diagram to relational schema Enhanced ER diagram: supertype and subtype, specialization, generalization, aggregation, various constraints, different ER notations, entity clustering ER diagram to relation: cardinality constraints to relational mapping, converting different types of attributes in relation, practice problems, Database Normalization: various anomalies, importance of normalization, functional dependency, partial dependency, transitive dependency, 1NF, 2NF, practice problems, 3NF, BCNF, practice problems. |
CO3 |
Text Books, Reference Books and Other Resources:
- Database System Concepts (7th Edition) by Silbarchatz
- Fundamentals of Database Systems (7th Edition) by Elmasri
- Database Management System (3rd Edition) by Ramakrishnan
- Modern Database Management (10th Edition) by Jeffrey A. Hoffer
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO2 |
PO2 |
C3 |
Lecture notes, PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO3 |
PO2, PO3, PO4 |
C6 |
Lecture notes, PPT slides |
Class Test, Midterm, Assignment, Final |
|
Course Title: Database Management System Laboratory |
|
Course Code: CSE 238 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
This course is designed to introduce the concept of real-world database design through the implementation of a database-driven real-time project.
Course Objectives:
- To facilitate necessary knowledge about the design of a database based on various scenarios.
- To develop a real-world database application.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Execute (C3) query language using database panel or application programming. |
|
CO2 |
Model (C3) a database for a given problem considering different anomalies. |
|
CO3 |
Develop (C6) and Report (A3) a database solution to an engineering problem as an individual or group project. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
√ |
√ |
||||||||
|
CO3 |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Familiarization with database management system, Basic, Intermediate and Advanced SQL queries, executing queries from application programming
|
CO1 |
|
2. |
Modeling: ER and EER, ER to relation, relation to ER, normalization |
CO2 |
|
3. |
Project: Activities, report, presentation slides.
|
CO3 |
Text Books, Reference Books and Other Resources:
- Database System Concepts (7th Edition) by Silbarchatz
- Fundamentals of Database Systems (7th Edition) by Elmasri
- Database Management System (3rd Edition) by Ramakrishnan
- Modern Database Management (10th Edition) by Jeffrey A. Hoffer
- Web references: w3schools.com, www.mysqltutorial.org
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO2, PO5 |
C3 |
Demonstration, PPT slides |
Lab Performance, Assignment |
|
CO2 |
PO2, PO3, PO4, PO5 |
C3 |
Demonstration, PPT slides |
Lab Performance, Assignment |
|
CO3 |
PO2, PO3, PO4, PO5, PO8, PO9, PO10, PO11, PO12 |
C6, A3 |
Demonstration, PPT slides |
Project Demo and Report |
|
Course Title: Signals & Systems |
|
Course Code: EEE 201 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: EM II |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course aims to provide basic knowledge about various types of signals and systems along with different analysis techniques.
Course Objectives:
The objectives of this course are:
- To help students conceptualize the relation between signals & systems.
- To make the students understand classification of signals & properties of systems.
- Accumulate basic ideas about analogous system and differential equations.
- Facilitate students with necessary knowledge to conceptualize the properties of Fourier Series
- Acquaint students with the basic theory of Fourier and Laplace transformation.
- Develop skills to apply Fourier and Laplace transformation to solve real-time problems.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Apply (C3) Linearity, Causality, Time invariance, Memory, Stability and Inevitability of any system. |
|
CO2 |
Analyze (C4) how signals transform from time domain to frequency domain & transform from frequency domain to time domain. |
|
CO3 |
Apply(C3) convolution on signals. |
|
CO4 |
Analyze(C4) how signals convert between mechanical system and electrical system. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Signals: Introduction to the Signals - classification, Basic operation on signals, Elementary signals. Representation of signals using impulse function. |
CO1 |
|
2. |
Introduction to Systems: Introduction to the Systems – classification. Properties of System. Identification of systems by analyzing properties. |
CO1 |
|
3. |
Analogues system: Analogues system and their solution, Linear mechanical elements, Element representation, D’Alembert’s Principle, F-V analogy, F-I analogy, Mechanical coupling Device, Electromechanical Systems.
|
CO4 |
|
4. |
Linear differential equation-I: Overview of linear differential equation-I, Solution of higher order linear differential equation with constant coefficient. |
CO1 |
|
5. |
Linear differential equation-II: Overview of linear differential equation-II, Solution of higher order linear differential equation with undetermined coefficient. |
CO1 |
|
6. |
Lumped element electrical systems: Lumped element electrical systems using linear differential equation-I Lumped element electrical systems using linear differential equation-II Lumped element electrical systems using linear differential equation-III |
CO4 |
|
7. |
Fourier Series: Overview of Fourier Series. Fourier series- properties, Harmonic representation, System response, Frequency response of LTI systems. |
CO2 |
|
8. |
Fourier transformation: Fourier transformation- properties, System transfer function, System response and distortion-less systems. Fourier transformation- Applications of time and frequency domain analyses: solution of analog electrical and mechanical systems. |
CO2 |
|
9. |
Laplace transformation: Fourier transformation to Laplace transformation (LT), LT of important functions. LT: gate function, LT of periodic functions. |
CO2 |
|
10 |
Application of Laplace Transformation: Application of Laplace Transformation, inverse transform, solution of system equations, system transfer function. Inverse Laplace Transform. LT: Impulse function, convolution integral, superposition integral. |
CO2 |
|
11 |
Convolution of Signals: Convolution of Signals. Introduction to Random signal, Stationery, Ergodicity, Noise models. Correlation and power spectrum, Distribution and density functions. |
CO3 |
Text Books, Reference Books and Other Resources:
- Signals and Systems by Haykin
- Linear System Analysis by D.K. Cheng.
- Signal & Systems Analysis using Transform Methods and MATLAB by M.J. Roberts
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final |
|
CO2 |
PO2 |
C4 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final |
|
CO3 |
PO1 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final |
|
CO4 |
PO2 |
C4 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Assignment, Midterm, Final |
|
Course Title: Signals and Systems Laboratory |
|
Course Code: EEE 202 |
|
Credits: 1 Class Hours/Week: 2 |
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Course Type: Core Pre-requisite: |
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CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
This course aims to develop students’ knowledge to implement different transform methods in MATLAB environment.
Course Objectives:
The objective of the course is to enable the students to
- Familiarize students with the MATLAB environment
- Introduce with plotting & sub-plotting concept.
- Learn simulation of Fourier, Laplace & Z-transformation.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
· Evaluate (A3, P4, C6) different types of Signals in Matlab or CAD tools. |
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CO2 |
Respond (A2, P2) in writing comprehensive reports on the work done in laboratory in a group and orally present the findings. |
Mapping of Course Outcomes to Program Outcomes:
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
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√ |
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CO2 |
√ |
√ |
√ |
Text and Reference books:
- Signals and Systems by Haykin.
- Linear System Analysis by D.K. Cheng.
- Signal & Systems Analysis using Transform Methods and MATLAB by M.J. Roberts
- Lab Manual
Course Description:
|
SL No |
Course Content |
CLOs |
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1. |
Laboratory work based on theory course EEE 201: Signals and Systems |
CO1 – CO2 |
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO5, PO12 |
A3, P4, C6 |
Lectures, Web |
Lab Performance, Quiz/Viva |
|
CO2 |
PO9, PO10, PO12 |
A2, P2 |
Discussion and Presentation |
Report and Presentation |
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Course Title: Computational Methods for Engineering Problems |
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Course Code: CSE 301 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: EM III |
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CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course is designed to make the understanding about computational concepts.
Course Objectives:
The objectives of this course are to:
- Provide knowledge for solving various scientific and engineering problems.
- Analyze and evaluate the accuracy of common numerical methods in its applications.
- Develop mathematical modeling skills for experiments and research.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Implement (C3) techniques to minimize errors of numerical methods. |
|
CO2 |
Use (C3) numerical techniques for solving linear and nonlinear complex optimization problems. |
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CO3 |
Implement (C3) complex systems of interpolation, curve fitting, and numerical differentiation and integration. |
|
CO4 |
Implement (C3) numerical algorithms for solving ordinary and partial differential equations. |
|
CO5 |
Apply (C3) numerical methods to solve problems in computational linear algebra, such as matrix operations and eigenvalue calculations. |
Mapping of Course Outcomes to Program Outcomes:
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
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CO2 |
√ |
√ |
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CO3 |
√ |
√ |
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CO4 |
√ |
√ |
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CO5 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
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1. |
Discuss Geometrical method to find real root of the equation, Bisection method, False position method, Fixed point iteration, Newton Raphson method, Solution of linear system, Difference table, Forward Difference table and Backward Difference table; Fundamental theorem of the difference Calculus, Interpolation with equal interval, Interpolation with unequal interval, Numerical Differentiation, Numerical Integration, Solution of Ordinary Differential Equations |
CO1 – CO5 |
Text Books, Reference Books and Other Resources:
- Numerical Analysis, by Vasistha
- Numerical Analysis, by Richard L. Burden,
- Numerical methods for scientific and engineering computation, by Mahinder Kumar Jain, R. K. Iyengar, Rajendra K. Jain
- Advanced Engineering Mathematics by H.K. Das
- Numerical Analysis, by Vasistha
- Numerical Analysis by Richard L. Burden
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C3 |
Lecture, Notes, Problem solution |
Class Test, Assignment, Midterm, Final Exam |
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CO2 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
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CO3 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
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CO4 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
|
CO5 |
PO1, PO2 |
C3 |
Lectures, Notes, Practice Problems |
Class Test, Assignment, Midterm, Final Exam |
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Course Title: Computational Methods for Engineering Problems Laboratory |
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Course Code: CSE 302 |
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Credits: 0.75 Class Hours/Week: 1.5 |
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Course Type: Core Pre-requisite: EM I, EM II, EM III |
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CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This course equips students with the knowledge and skills to solve complex mathematical problems encountered in computer science using efficient and accurate numerical techniques.
Course Objectives:
The objectives of the course are:
- To brings light the numerous uses of numerical methods in engineering.
- To obtain error estimates for numerical derivative formulae.
- To demonstrate implementation of numerical problems for engineering problems
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Apply (C3) numerical methods for solving engineering problems. |
|
CO2 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
√ |
√ |
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CO2 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Lab based on theory course of Computational Methods for Engineering Problems |
CO1, CO2 |
Text Books, Reference Books and Other Resources:
- Computer Networking: A Top-Down Approach---- (James F. Kurose, Keith W. Ross)-- Instructor contents and PPT slides: http://gaia.cs.umass.edu/kurose_ross/instructor.php
- Cisco Packet Tracer Simulation
- Additional contents: Cisco PowerPoint slides, pdf tutorials will be provided.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C3 |
Lecture, Laboratory Experiments |
Quiz, Performance, Assignment |
|
CO2 |
PO10 |
A3 |
Lecture, Laboratory Experiments |
Quiz, Performance, Assignment |
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Course Title: Software Engineering & Information System Design |
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Course Code: CSE 305 |
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Credits: 4 Class Hours/Week: 4 |
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Course Type: Core Pre-requisite: DMS |
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CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Software Engineering and Information Systems is a profile where the software development is studied in a systematic, controllable and efficient way.
Course Objectives:
The objectives of this course are:
- To introduces the concept and method required for the construction of large software intensive system. It aims to develop a broad understanding of the discipline of software engineering.
- To complement this with detail knowledge of technique for the analysis and design of complex software system. It aims to set these techniques in an appropriate engineering and management context.
- To provide a brief account of associated professional and legal issues.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Explain (C2) different concepts of software engineering and information system design. |
|
CO2 |
Describe (C2) conventional and agile software engineering process models. |
|
CO3 |
Illustrate (C3) different modeling techniques to represent the working process of a software system. |
|
CO4 |
Demonstrate (C3) different types of software testing strategies. |
|
CO5 |
Illustrate (C3) various types of software project variables to estimate software project and maintaining project risks for quality improvement. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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CO2 |
√ |
√ |
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CO3 |
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√ |
√ |
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CO4 |
√ |
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CO5 |
√ |
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Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction Software Engineering Introduction to Software Engineering, Purpose, Applications, failure curves, software applications, legacy software, Umbrella Activities. |
CO1 |
|
2. |
Software Process Model: Process Flow, Process Models (RAD, Waterfall, Incremental, Spiral, Agile, Prototype, Concurrent), Advantages, Disadvantages, Framework Activities, Task set, Agile Development, Agility, Human Factors, Extreme Programming |
CO1, CO2 |
|
3. |
Unified Modeling Language: Notations and basic concepts, Use Case Diagram, Sequence Diagram, Activity Diagram |
CO3 |
|
4. |
Software Testing: Exhaustive Testing, Selective Testing, Good Test, Testing Principles, Black box Testing, White box Testing, Equivalence Partitioning, Boundary Value Analysis, Cause-Effect, Unit Testing, Integration Testing, System Testing Graphing, Testing, Error, Fault, Failure, Acceptance Testing |
CO4 |
|
5. |
Estimation and Software Risk: Introduction to software project variables, project estimation, risk management, software quality management |
CO5 |
|
6. |
Information System Design: Information System Design Life Cycle, Requirements engineering, Role and attributes of a system analyst, Feasibility Analysis, Data Flow Diagrams, Document Flow Diagrams, Process specification, Data Input Methods
|
CO1, CO3, CO5 |
Text Books, Reference Books and Other Resources:
- Analysis and Design of Information Systems (2nd Edition) V. Rajaraman.
- Software Engineering: A Practitioner’s Approach (8th Edition) R. S. Pressman.
- Software Engineering (9th Edition) Martin Shooman.
- Software Engineering (9th Edition) by Ian Sommerville
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Textbook, slides |
Class test, Midterm, Assignment, Final |
|
CO2 |
PO1, PO2 |
C2 |
Lecture, Textbook, slides |
Class test, Midterm, Assignment, Final |
|
CO3 |
PO2, PO3 |
C3 |
Lecture, Textbook, slides |
Class test, Midterm, Assignment, Final |
|
CO4 |
PO1 |
C3 |
Lecture, Textbook, slides |
Class test, Midterm, Assignment, Final |
|
CO5 |
PO1 |
C3 |
Lecture, Textbook, slides |
Class test, Midterm, Assignment, Final |
|
Course Title: Software Engineering & Information System Design Laboratory |
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Course Code: CSE 306 |
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Credits: 1.5 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: DMSL |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
Software Engineering and Information Systems is a profile where the software development is studied in a systematic, controllable and efficient way.
Course Objectives:
The objectives of the course are:
- To impart state-of-the-art knowledge on Software Engineering and UML in an interactive manner through the Web.
- To present case studies to demonstrate practical applications of different concepts.
- To provide a scope to students where they can solve small, real life problems.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Use (C3) appropriate tools for managing a software project. |
|
CO2 |
Implement (C3) various client-side and server-side concepts utilizing design pattern to develop a software. |
|
CO3 |
Investigate (C4) a system and Report (A2) the overall working process using modern tools. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
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√ |
||||||||||
|
CO2 |
√ |
√ |
√ |
√ |
||||||||
|
CO3 |
√ |
√ |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Project Management: Project collaboration, Task Management |
CO1 |
|
2. |
Implementation: Client side and server-side feature implementation, design pattern and modular approach, software testing |
CO2 |
|
3. |
System Modeling: Project Proposal, Process model selection, UML diagram design, SRS document |
CO3 |
Text and Reference Books:
- Head First Design Patterns by Eric Freeman, Elisabeth Robson, Bert Bates, Kathy Sierra
- Downloaded Software Engineering with UML by Bhuvan Unhelkar
- Practical UI Patterns for Design Systems. Fast-Track Interaction Design for a Seamless User Experience by Diana MacDonald
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO5 |
C3 |
Lecture, slides |
Class performance, Assignment, Report |
|
CO2 |
PO1, PO2, PO3, PO5 |
C3 |
Lecture, slides |
Class performance, Assignment, Report |
|
CO3 |
PO2, PO4, PO5, PO9, PO10 |
C4, A2 |
Lecture, slides |
Class performance, Assignment, Report |
|
Course Title: Communication Engineering |
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Course Code: EEE 309 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This Course is offered to introduce the basic principles and applications of analog and digital
communication in our daily life.
Course Objectives:
The objectives of this course are:
- To introduce students with the fundamental concepts of communication systems.
- To provide the knowledge of different analog modulation schemes and digital modulation schemes.
- To make the students understand the multiple access techniques and key aspects of noise.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Explain (C2) different types of analog modulation and digital modulation |
|
CO2 |
Solve (C3) mathematical problems related to Communication engineering. |
|
CO3 |
Analyze (C4) various channels and noises of communication system. |
|
CO4 |
Analyze (C4) graphical and mathematical system of multiplexing & De-multiplexing. |
|
CO5 |
Design (C6) Communication system |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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CO2 |
√ |
√ |
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CO3 |
√ |
|||||||||||
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CO4 |
√ |
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|
CO5 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction of communication systems: Basic principles, fundamental elements, system limitations. |
CO2 |
|
2. |
Information Theory: Information and system capacity, Information transmission, Entropy, Continuous channel capacity, Transmission through electrical network. |
CO2 |
|
3. |
Analog communication: AM, FM, PM, DSB, SSB, VSB, ISB. |
CO1 |
|
4. |
Digital communication: Introduction, Nyquist sampling theorem, Quantization of analog system, Quantization noise, PAM, PWM, PPM, PCM, LOGPCM, and systems, Digital modulations, ASK, FSK, PSK, DPSK, MSK, M-array digital modulation, QAM, QPSK, Delta modulation, Multi carrier modulation, line coding, Frame construction, Error Probability. Introduction to Radar and Satellite Communication. ISDN, B-ISDN, SONET, SDH modulations, ASK, FSK, PSK, DPSK, MSK, M-array digital modulation, QAM, QPSK, Delta modulation, Multi carrier modulation, line coding, Frame construction, Error Probability. Introduction to Radar and Satellite Communication. ISDN, B-ISDN, SONET, SDH |
CO1, CO5 |
|
5. |
Multiplexing: Space division multiplexing, frequency division multiplexing, time division multiplexing, and code division multiplexing. |
CO4, CO5 |
|
6. |
Noise: Physical sources of noise, types of noise, calculation of noise, SNR & noise figure, and calculation of noise figure, noise temperature, equivalent noise resistance. |
CO3 |
Text Books, Reference Books and Other Resources:
- Electronic Communication System by George Kennedy.
- Modern Digital & Analog Communication Systems by B.P. Lathi.
- Communication System by Simon Haykin.
- Principles of Communication Systems by Herbert Taub and Donald L. Schilling
CO Delivery and Assessment:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, PPT slide, Mathematical Problem solving |
Class Test, Assignment, Mid Term, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture, PPT slide, Mathematical Problem solving |
Class Test, Assignment, Mid Term, Final Exam |
|
CO3 |
PO2 |
C4 |
Lecture, PPT slide, Mathematical Problem solving |
Class Test, Assignment, Mid Term, Final Exam |
|
CO4 |
PO2 |
C4 |
Lecture, PPT slide, Mathematical Problem solving |
Class Test, Assignment, Mid Term, Final Exam |
|
CO5 |
PO2 |
C6 |
Lecture, PPT slide, Mathematical Problem solving |
Class Test, Assignment, Mid Term, Final Exam |
|
Course Title: Communication Engineering Laboratory |
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Course Code: CSE 310 |
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Credits: 1.5 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
This course aims to introduce students with basic techniques and tools for electrical circuit simulation.
Course Objectives:
The objective of the course is to enable the students to
- To develop knowledge of using simulation tools for simulating electric circuit.
- To distinguish the difference between the simulation behavior and behavior of practical circuit.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C5, A4, P3) different types of analog and digital modulation and demodulation techniques using experimental setup as an individual or as a member of a team. |
|
CO2 |
Conclude (C6, A3, P1) the result from experimental data. |
|
CO3 |
Interpret (A4, P2) the laboratory work done in a group to present the findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
√ |
|||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Laboratory work using hardware based on theory course: EEE 309: Communication Engineering. It will cover AM FM, ASK, FSK, PSK modulation and demodulation practical laboratory work. |
CO1, CO2, CO3 |
|
2. |
Report writing based on laboratory work. |
CO3 |
|
3. |
Oral presentation on mini project work (design project/analytical project/ experimental project/industrial tour). |
CO1, CO2 |
Text and Reference books:
- Lab Manuals
- Additional contents: Communication Engineering PowerPoint slides, pdf tutorials will be provided.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO5, PO9, PO10 |
C5, A4, P3 |
Lecture, Demonstration, discussion, experiment |
Quiz/Written Exam, Performance, Report |
|
CO2 |
PO4, PO12 |
C6, A3, P1 |
Lecture, Calculation, Graph Drawing, Report |
Class Performance, Report |
|
CO3 |
PO9, PO10, PO12 |
A4, P2 |
Lecture, Mini Project, Presentation, Report Writing |
Class Performance, Quiz/Written Exam, Presentation |
|
Course Title: Microprocessors and Microcontrollers |
|
Course Code: EEE 371 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: DE |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Intended to enable the learners to familiar with different types of microprocessors and microcontrollers, use the acquired knowledge to understand computer systems and embedded systems circuitry or architectures.
Course Objectives:
The objectives of this course are to:
- Provide a theoretical &empirical introduction to microcontrollers and microprocessors, assembly language programming techniques, design of hardware interfacing circuit, microcontroller, and microprocessor system design considerations.
- Provide the rudimentary concepts to identify the basic elements and functions of contemporary microprocessors and microcontrollers and implicating programming in the instruction sets of microprocessors and microcontrollers (Basically Intel family).
- Designing and maintaining different types of digital projects to fulfill the quotidian life problem in embedded system.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Describe (C2) the basics of microprocessor and microcontroller architecture, interfacing, and operations. |
|
CO2 |
Execute (C3) assembly language instructions or programs to control microprocessor and microcontroller operations. |
|
CO3 |
Solve (C3) the real-world problems related with embedded systems and designs. |
|
CO4 |
Illustrate (C2) microprocessor and microcontroller related circuitry and sensor interfacing. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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CO2 |
√ |
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CO3 |
√ |
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CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to different type of microprocessors: 8 bit, 16 bit, 32 bit and their architectures; pin diagram & junction; Intel series microprocessor and Co-processor; RISK & CISK processor; Assembly Language: Basic Instruction Sets and Assembly language Programming based on 8086 microprocessor. |
CO1 |
|
2. |
Microprocessor peripherals: Introduction to some available microprocessor peripherals IC's and their application such as 8251, 8253, 8254, 8255, 8257, 8259, 8279, A/D and D/A converter interfacing, Timing Diagram, Interrupts, I/O systems, DMA-based data transfer, memory interfacing. MMX and SIMD technologies. The above peripheral is based on 8085 and 8086 processor. |
CO2 |
|
3. |
Interfacing: Introduction, interfacing to microprocessor to keyboards, alphanumeric displays. Introduction to microcomputers and interfacing to microcomputer ports to high power devices. |
CO3 |
|
4. |
Basic Micro controller: Introduction of microcontroller; embedded system design; microcontroller programming environment; Architecture of different microcontroller such as PIC, MSP, ARM etc. Real time application design based on microcontroller. |
CO3, CO4 |
|
5. |
PIC Microcontroller: Introduction to PIC Microcontroller, Internal Architecture, Components & Programming. Some PIC Based Project work. |
CO3, CO4 |
|
6. |
Arduino & Raspberry Pi: Introduction of Development boards. |
CO3, CO4 |
Text Books, Reference Books and Other Resources:
- The Intel Microprocessor Architecture, Programming and Interfacing, Barry B. Brey.
- Microprocessors and Interfacing: Programming and Hardware,Douglas V. Hall.
- Advanced Microprocessor and Interfacing, Badri Ram.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment tools |
|
CO1 |
PO1 |
C2 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1 |
C3 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO3 |
C3 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO4 |
PO1 |
C2 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Microprocessors and Microcontrollers Laboratory |
|
Course Code: EEE 372 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: DEL |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
The course is intended to introduce the basic concepts of microprocessor and to develop in students the assembly language programming skills and real time applications of Microprocessor as well as microcontroller.
Course Objectives:
The objectives of this course are to:
- Learn about different types of microcontroller & Microprocessors
- Gather knowledge about different types of sensors used in our day-to-day life.
- Learn about microcontroller programming.
- Design simple project based on microcontroller
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Describe (P1) and write program in assembly language for 8086 microprocessors. |
|
CO2 |
Design (C3, P3) micro-controller based Real Time Projects |
|
CO3 |
Design (C3, P3) SBC based system. |
|
CO4 |
Perform work (C6, A3, P3) in individual and or group project. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Study on micro controller and tinkercad simulator |
CO1 |
|
2. |
Familiarizing with Arduino, Arduino IDE & design a simple LED looping Circuit. |
CO2 |
|
3. |
Interfacing with stepper motor. |
CO2 |
|
4. |
Keyboard & LCD display interfacing |
CO2 |
|
5. |
PWM & its use in Arduino using Servo Motor. |
CO2 |
|
6. |
Interfacing with different types of sensors with Arduino module |
CO2 |
|
7 |
Interfacing with Bluetooth module |
CO2 |
|
8 |
Introduction to Single board computer (SBC) |
CO3, CO4 |
|
9 |
Project Work |
CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Lab manual
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
P1 |
Lecture, Slide, Problem Solving, and examples |
Quiz, Performance Test |
|
CO2 |
PO3, PO5 |
C3, P3 |
Lecture, Slide, Problem Solving, and examples |
Quiz, Performance Test |
|
CO3 |
PO3, PO5 |
C3, P3 |
Lecture, Slide, Problem Solving, and examples |
Quiz, Performance Test |
|
CO4 |
PO3, PO5, PO9, PO10 |
C6, A3, P3 |
Lecture, Slide, Problem Solving, and examples |
Project submission, Presentation |
|
Course Title: Artificial Intelligence |
|
Course Code: CSE 317 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course introduces the basic concepts and techniques of Artificial Intelligence (AI) to creating software and hardware to get computers to do things that would be considered intelligent as if people did them.
Course Objectives:
- Introducing the students to AI’s fundamental problems and state-of-the-art algorithms.
- Appreciating the role of knowledge representation, logic, and language in understanding human intelligence from a computational perspective.
- Helping the students conceptualize the far-reaching goal of AI in shaping our future.
- Exposing the students to the frontiers of AI-intensive computing while providing a sufficiently strong foundation to encourage further research.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Interpret (C2) the key components and classical search algorithms of AI to solve various real-life problems. |
|
CO2 |
Investigate (C4) statistical methods and machine learning techniques for solving complex AI-related problems |
|
CO3 |
Use (C3) Natural Language Processing methods for real-life problem solving. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Artificial Intelligence AI Subfields, AI agent, Task Environment, Environment Type |
CO1 |
|
2. |
Searching Techniques: BFS, DFS, UCS, Best First Search, A*, Genetic Algorithm |
CO1 |
|
3. |
Introduction to Natural Language Processing (NLP) Introduction, Intuitions, Application Fields, Text Representation, Different Language Models (char/word n-grams), Text Similarity Measure, Machine Translation. |
CO3 |
|
4. |
Introduction to Uncertainty Quantifying Uncertainty, Basic Probability Notation, Inference using full joint distributions, Bayes Rule, Semantics of Bayesian network (BN), Inference in BN, Probabilistic Reasoning over time, Hidden Markov Models. |
CO2 |
|
5. |
Introduction to Learning Nearest Neighbors, Linear Regression, Logistic Regression, Decision Tree, K Means Clustering, Naïve Bayes Classifier, Reinforcement Learning |
CO2 |
Text Books, Reference Books and Other Resources:
- "Artificial Intelligence – A Modern Approach", by Stuart Russell and Peter Norvig.
- "Speech and Language Processing", Jurafsky & Martin, Third Edition (Draft Link)
- "Artificial Intelligence",by Elaine Rich, Kevin Knight.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1, PO2 |
C4 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1, PO2, PO5 |
C3 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
Course Title: Artificial Intelligence Laboratory |
|
Course Code: CSE 318 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
This subject aims to practically implement as well as analyze the various procedures, methods, and algorithms related to artificial intelligence for real-world applications.
Course Objectives:
The objective of the course is to enable the students to
- Provide students with a practical aspect of various AI algorithms
- Motivate them towards developing their careers in AI applications
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
· Demonstrate (C2) the application of modern tools for data preprocessing and analysis. |
|
CO2 |
Apply (C3) search strategies for solutions to problems with complete information. |
|
CO3 |
· Develop (C3) an intelligent system capable of learning from data. |
|
CO4 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
√ |
|||||||||
|
CO2 |
√ |
√ |
√ |
|||||||||
|
CO3 |
√ |
√ |
√ |
√ |
||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Python Basic Syntax, Functions, Machine Learning Tools |
CO1 |
|
2. |
Search Techniques Implementation: Uninformed Search Techniques, Informed Search Techniques |
CO2 |
|
3. |
Project Implementation Text Data Reading and Preprocessing, Text Representation, Model Implementation |
CO3 |
Text and Reference books:
- "Artificial Intelligence – A Modern Approach", by Stuart Russell and Peter Norvig
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C2 |
Lecture, Lab Task |
Lab Performance, Assignment |
|
CO2 |
PO1, PO2, PO5 |
C3 |
Lecture, Lab Task |
Lab Performance, Assignment |
|
CO3 |
PO1, PO2, PO3, PO9 |
C3 |
Lecture, Web links |
Project Report, Performance, Presentation, Viva |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Operating Systems |
|
Course Code: CSE 333 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course provides a comprehensive understanding of the modern Operating System and examines the ways that design goals can be achieved.
Course Objectives:
The objectives of this course are:
- To enhance students' understanding of the function and structure of operating systems
- To facilitate necessary knowledge about how the system interacts and provides services for the execution of application software.
- To evaluate underlying hardware, virtual memory, concurrency, and synchronization.
- To enable them to illustrate key operating system aspects by concrete examples, and prepare them for future courses.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) the basic structure and characteristics of a modern operating system, the concept for virtualization, cloud, and multiple processor systems. |
|
CO2 |
Explain (C2) the different process and thread synchronization methods and the tradeoffs between them. |
|
CO3 |
Assess (C4) the algorithms on which the functions of the Operating Systems are built. |
|
CO4 |
Compare (C3) different types of memory-management schemes for a system. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Operating system, Computer-system organization, and architecture, Operations, Computing environments. |
CO1 |
|
2. |
Operating-System Structures: Operating system services, System calls, Operating system structure. |
CO1 |
|
3. |
Processes: Process concept, Process scheduling, Operations on processes, Communication |
CO2 |
|
4. |
Multithreaded Programming: Threading overview, Multithreading models |
CO2 |
|
5. |
Process Scheduling: Basic concept, Criteria, Algorithms |
CO3 |
|
6. |
Deadlocks: Characterization, Methods for handling deadlocks, Deadlock Prevention, Avoidance, Detection. |
CO3 |
|
7. |
Main Memory: Background, Swapping, Segmentation, Paging |
CO4 |
|
8. |
Virtual Memory: Background, Demand Paging, Page replacement |
CO4 |
|
9. |
File System Interface: File Concept, Access methods, Directory structure |
CO1 |
3
Text Books, Reference Books, and Other Resources:
- Abraham Silberschatz, Peter Baer Galvin, Greg Gagne, “Operating System
Concepts”, (8th Edition) ISBN: 978-0-470-23399-3. - Andrew S. Tanenbaum (Author), Herbert Bos, “Modern Operating Systems”
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Problem solution |
Assignment, Class Test, Midterm, Final |
|
CO2 |
PO1, PO2 |
C2 |
Lecture, Problem solution |
Assignment, Class Test, Midterm, Final |
|
CO3 |
PO1, PO2 |
C4 |
Lecture, Problem solution |
Assignment, Class Test, Midterm, Final |
|
CO4 |
PO1, PO2 |
C3 |
Lecture, Problem solution |
Assignment, Class Test, Midterm, Final |
|
Course Title: Operating Systems Laboratory |
|
Course Code: CSE 334 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
This course provides a comprehensive understanding of the modern Operating System and examines the ways that design goals can be achieved.
Course Objectives:
The objectives of this course are to:
- Learn and use the shell commands of Operating Systems.
- Familiarize students with the architecture of an OS.
- Provide necessary skills for developing and debugging programs in different environments.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Interpret (C2) directory operation using GUI & Terminal. |
|
CO2 |
Use (C3) different shell commands for basic system operation. |
|
CO3 |
Configure (C3) different servers (such as Web, DNS, FTP, Email, etc.) through the knowledge gained in this course. |
|
CO4 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to various Operating Systems |
CO1, CO4 |
|
2. |
Basic Overview of Boot Process |
CO1, CO4 |
|
3. |
User management and Basic Shell commands |
CO1, CO4 |
|
4. |
Essential Commands |
CO1, CO4 |
|
5. |
Advanced commands & tools for System Administration |
CO1, CO4 |
|
6. |
Shell script and Scheduling |
CO1, CO4 |
|
7. |
Configuring a basic server |
CO1, CO4 |
Text Books, Reference Books, and Other Resources:
- Red Hat Enterprise Linux 6 Administration By Sander Van Vugt.
- https://linuxconfig.org
- https://www.linuxfoundation.org
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Demonstration, discussion, experiment |
Assignment, Performance |
|
CO2 |
PO1 |
C3 |
Demonstration, discussion, experiment |
Assignment, Performance, Report, Quiz |
|
CO3 |
PO3 |
C3 |
Demonstration, discussion, experiment |
Assignment, Performance, Lab Exam |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Computer Organization & Architecture |
|
Course Code: CSE 337 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Intended to enable the learners to gather proper knowledge in hardware design by
understanding the fundamentals of core and modern computer architectures and hardware.
Course Objective:
The objectives of this course are:
- To understand the basic structure and operation of a digital computer.
- To familiarize students with hardware design and the operation of the arithmetic unit including the algorithms.
- To learn different ways to communicate with I/O devices and standard I/O interfaces.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to-
|
CO1 |
Describe (C2) the basics of computer hardware and how software interacts with computer hardware. |
|
CO2 |
Demonstrate (C2) computer performance using various assessing methods. |
|
CO3 |
Explain (C2) how computers represent and manipulate data. |
|
CO4 |
Assemble (C3) a simple computer with hardware design including data format, instruction format, instruction set, addressing modes, bus structure, input/output, memory, arithmetic/logic unit, control unit, and data, instruction and address flow. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Instructions: Language of the computer, introduction, Operations of the Computer Hardware, Operands of the Computer Hardware, Representing Instructions in Computer, Logical Operations. |
CO1 |
|
2. |
Assessing and Understanding Performance: CPU Performance and its Factors, Evaluating Performance, Fallacies and Pitfalls. |
CO1 |
|
3. |
Basic Computer Organization & Design: Instruction Codes, Direct/Indirect Address, Computer Registers and Bus systems |
CO2 |
|
4. |
Design of a Basic Computer: Computer Instruction, Timing and Control, Instruction Cycle, Interrupts |
CO2 |
|
5. |
Enhancing Performance with Pipelining: An overview of Pipelining, A Pipelined Datapath, Pipelined Control, Data Hazards and forwarding, Branch Hazards, Fallacies and Pitfalls |
CO3 |
|
6. |
Central Processing Unit: General Register Organization, Stack Organization, Instruction Formats, Reverse polish notation, Instruction Formats, Address Instructions, Addressing Modes, Data Transfer and Manipulations. |
CO3 |
|
7. |
Computer Arithmetic: Multiplication Algorithm, Division Algorithm, Floating-Point Arithmetic Operation. |
CO3 |
|
8. |
I/O Organization: I/O Interface, Asynchronous Data Transfer, Strobe Control Handshaking, Asynchronous Serial Transfer, Asynchronous Communication Interface, DMA, DMA Controller, DMA Transfer in a computer system |
CO4 |
|
9. |
Memory Organization: Memory Hierarchy, Main Memory, Auxiliary Memory, Cache Memory, Memory Mapping |
CO4 |
|
10. |
Multiprocessors: Characteristics of multiprocessors, Interconnection Structures, Cache Coherence |
CO4 |
Text Books, Reference Books, and Other Resources:
- Morris Mano, “Computer System Architecture”, 3rd Edition, Prentice-Hall India, 2003, ISBN-81-203-0855-7
- David A. Patterson, “Computer Organization and Design”, 3rd Edition.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Slide Presentation |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1 |
C2 |
Lecture, Slide Presentation |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1 |
C2 |
Lecture, Slide Presentation |
Class Test, Assignment, Midterm, Final Exam |
|
CO4 |
PO1, PO2, PO3 |
C3 |
Lecture, Slide Presentation |
Class Test, Assignment, Midterm, Final Exam |
|
Course Title: Software Development |
|
Course Code: CSE 338 |
|
Credits: 2 Class Hours/Week: 4 |
|
Course Type: Core Pre-requisite: DMS |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
In the Software Development course, the students will learn how to build software from scratch. The program focuses on developing responsive designs, validation and testing, analyzing different methods for solving a particular problem, working in a group for continuous delivery etc. Students will learn about the latest project management tools, how to model a problem from various domains.
Course Objectives:
The objectives of this course are:
- To contribute effectively to the development process of a c
- To make students eligible to deal with changes during the middle of the development of software.
- To prepare students to adapt to new technologies in the future.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
· Implement (C3) various server-side and client-side concepts using latest framework. |
|
CO2 |
Use (C3) 3rd party packages for developing software. |
|
CO3 |
· Work (A4) in an individual or group project maintaining engineering ethics. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
√ |
|||||||||
|
CO2 |
√ |
√ |
√ |
|||||||||
|
CO3 |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Familiarization to development framework, Client-side technologies, Server-side technologies, Report Writing with LATEX, Project Requirements |
CO1, CO2, CO3 |
|
2. |
Server-side and Client-side concepts: Design pattern, Routing, Interaction with database, CRUD operation, Authentication and Authorization, Validation, File Uploading, Client-Server Communication, API integration, Responsive Designs, 3rd Party package Integration |
CO1, CO2 |
|
3. |
Project: Requirements analysis, identifying scopes, modeling the specifications, implementation, and representing all the steps via report |
CO3 |
Text Books, Reference Books, and Other Resources:
- World-wide web, YouTube Tutorials
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C3 |
Demonstration, experiment |
Performance, Assignment |
|
CO2 |
PO1, PO2, PO5 |
C3 |
Demonstration, experiment |
Performance, Assignment |
|
CO3 |
PO1, PO2, PO3, PO4, PO5, PO6, PO7 PO8, PO9, PO10, PO11, PO12 |
A4 |
Project Related Instruction |
Project, Report, Presentation |
|
Course Title: Data Communication |
|
Course Code: CSE 364 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: |
|
CIE Marks: 60 SEE- Marks: 40 |
Course Rationale:
Data communication, which is the transmission of digital data through a network or to a device external to the sending device, is the cornerstone of modern telecommunications. Given the importance of different communication systems, this course is designed for Computer Science and Engineering students.
Course Objectives:
- Enable the students to understand the fundamental concepts and techniques of Data Communication.
- Equip the skill required to apply encoding and communication protocols.
- Facilitate students to analyze the error detection and correction techniques.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Discuss (C2) the concepts of data communication systems and their components. |
|
CO2 |
Explain (C2) the digital and analogue representations and channels. |
|
CO3 |
Demonstrate (C3) the mechanism and techniques of encoding. |
|
CO4 |
Describe (C2) the general principles of communication protocol switching techniques |
|
CO5 |
Implement (C3) different error detection, correction and flow control techniques. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
|||||||||||
|
CO5 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Data Communications, components, Data Representation, Data Flow |
CO1 |
|
2. |
Data and Signals: Analog and Digital, Periodic Analog signals, Digital Signals, Time and Frequency Domain, Composite Signal. Bandwidth, Digital Signal, Transmission of digital signal, Transmission Impairment, Noise, SNR. Data Rate Limits, capacity Theorem, Nyquist Bit rate, Shannon Bit rate. Performance, bandwidth Delay Product. |
CO2 |
|
3. |
Modulation and demodulation: amplitude modulation, frequency and phase Modulation Analog Transmission: Digital-to-Analog Conversion, Constellation Diagram |
CO3 |
|
4. |
Modulation and demodulation: amplitude modulation, frequency and phase Modulation Analog Transmission: Digital-to- Analog Conversion, Constellation Diagram |
CO3 |
|
5. |
Bandwidth Utilization: Multiplexing, Analog Hierarchy, Interleaving, Data Rate Management, Digital Hierarchy STDM, Spread Spectrum |
CO2 |
|
6. |
Error Detection and Correction: Introduction, Single Bit Error, Burst Error, Detection Vs Correction, Forward Error correction Vs retransmission, Block Coding Hamming Distance, Linear Block Codes, Flow control techniques. |
CO5 |
|
7. |
Circuit and Packet Switching techniques, different communication protocols |
CO4 |
Text and Reference books:
- Data Communication and Networking by Behrouz A Forouzan
- Data and Computer Communications (9th Edition), by William Stallings, Publishers: Prentice Hall
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lectures/Instructions Reading Materials/PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO2 |
PO1 |
C2 |
Lectures/Instructions Reading Materials/PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO3 |
PO1 |
C3 |
Lectures/Instructions Reading Materials/PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO4 |
PO1 |
C2 |
Lectures/Instructions Reading Materials/PPT slides |
Class Test, Midterm, Assignment, Final |
|
CO5 |
PO1 |
C3 |
Lectures/Instructions Reading Materials/PPT slides |
Class Test, Midterm, Assignment, Final |
|
Course Title: Computer Networks |
|
Course Code: CSE 367 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course aims to introduce the basic concept and essential knowledge of computer networks.
Course Objectives:
The objectives of this course are:
- Building an understanding of the fundamental concepts of computer networking.
- Familiarizing the student with the basic taxonomy and terminology of the computer networking area.
- Introducing the students to advanced networking concepts, preparing the student for getting entry into advanced courses in computer networking.
- Allowing the students to gain expertise in some specific areas of networking such as the design and maintenance of individual networks.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Interpret (C2) the OSI and TCP/IP layered architecture, different TCP/IP layer protocols, network organization, the operations of the key networking components, advance network architecture: software defined networking, 4G/5G, etc. |
|
CO2 |
Describe (C2) the functionalities and performance of different routing and transport layer protocols, flow and congestion control mechanisms, link layer protocols, error detection and correction mechanisms, OpenFlow protocols. |
|
CO3 |
Practice (C3) the acquired knowledge to configure/design wired/wireless networks and sub-networks, routing protocols, security principles to networking, solve different network issues, etc. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Computer Networks and the Internet: Operations: protocol layers, service models, Performance Metrices: delay, loss, throughput |
CO1 |
|
2. |
Application Layer: Principles of network applications, Web and HTTP, electronic mail SMTP, POP3, IMAP, DNS, socket programming with UDP and TCP |
CO1, CO2 |
|
3. |
Transport Layer: Transport-layer services, 3.2 multiplexing and demultiplexing, connectionless transport: UDP function, The TCP Connection, TCP Segment Structure, Round-Trip Time Estimation and Timeout, Reliable Data Transfer, Flow Control, TCP Connection Management, TCP Congestion Control: Classic TCP Congestion Control Slow start, congestion avoidance, fast recovery 3.7.1 Classic TCP Congestion Control Slow start, congestion avoidance, fast recovery 3.7 TCP Congestion Control 3.7.1 Classic TCP Congestion Control Slow start, congestion avoidance, fast recovery Week 6 Problem Solving Week 6 Concept Checking Wireshark Lab TCP Project 1 Web Server submission Week 6 Lab Report - TCP Project A Review Quiz 3 6 3.5.5 Flow Control 3.5.6 TCP Connection Management 3.7 TCP Congestion Control 3.7.1 Classic TCP Congestion Control Slow start, congestion avoidance, fast Recovery |
CO1, CO2, CO3 |
|
4. |
Network Layer: Data Plane Overview of Network layer, data plane, control plane, What’s inside a router? IP: Internet Protocol, datagram format, Fragmentation, IPv4 addressing, network address translation, IPv6 , Components of SDN Controller, OpenFlow protocol, Traffic engineering, difficult with traditional routing |
CO2, CO3 |
|
5. |
Network Layer: Control Plane Introduction, routing protocols, link state, distance vector, intra-AS routing in the Internet: OSPF, routing among the ISPs: BGP |
CO2, CO3 |
|
6. |
The Link Layer and LANs Link Layer introduction, services, The Services Provided by the Link Layer, Where Is the Link Layer Implemented? Error-Detection and -Correction Techniques: Parity Checks, Multiple Access Links and Protocols: Channel Partitioning Protocols, Random Access Protocols, Taking-Turns Protocols, Switched Local Area Networks: Link-Layer Addressing and ARP, MAC Addresses, Address Resolution Protocol (ARP), Sending a Datagram off the Subnet, Ethernet, Ethernet Frame Structure, Ethernet Technologies, Link-Layer Switches: Forwarding and Filtering, Self-Learning, Properties of Link-Layer Switching, Switches Versus Routers, VLAN, Port based VLANs, VLANs spanning multiple switches: Trunk link |
CO1, CO2, CO3 |
|
7. |
Wireless and Mobile Networks: Elements of a wireless network, Wireless network taxonomy, Wireless link characteristics, Hidden Terminal Problem and signal attenuation, CDMA, 802.11, IEEE 802.11 MAC Protocol, Personal area networks, Network Security: Possible attacks on networks and possible ways to fight with those attacks |
CO1, CO2 |
Text Books, Reference Books and Other Resources:
- Computer Networking: A Top-Down Approach---- (James F. Kurose, Keith W. Ross)
Instructor contents and PPT slides: http://gaia.cs.umass.edu/kurose_ross/instructor.php
- TCP/IP illustrated. --- (Richard Stevens)
- Data Communications and Networking: The Basic Toolbox--- (Behrouz A. Forouzan)
- Computer Networks--- (Andrew S. Tanenbaum and David J)
- Additional contents: Cisco PowerPoint slides, pdf tutorials will be provided.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Computer Networks Laboratory |
|
Course Code: CSE 368 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ICS |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This subject aims to teach an understanding of computer networks and systems design through hands-on lab works and analysis with real world applications.
Course Objectives:
The objective of the course is to enable the students to
- Understand and implement the functionalities of major networking components, network topologies, and connections.
- Become familiar with configuration of networking and routing protocols, network operations, state-of-the-art developments and applications.
- Administer advanced topics such as WLAN, network security, threats mitigation, security best practices, network management, and/or other topics.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
· Identify (C1) basic networking and end devices: real equipment and simulation, install a home or small business network, connection to the Internet. |
|
CO2 |
Illustrate (C2) different application layer protocols, distance vector and link-state routing protocols, and transport layer protocols |
|
CO3 |
· Enhance (C2, A3) network security using access control lists and security best practices. |
|
CO4 |
· Use (C3) the acquired knowledge to establish, verify and troubleshoot network and Internet connectivity. |
|
CO5` |
· Complete (P3) different types of network cables and device connections by hands-on. |
|
CO6 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
√ |
|||||||||
|
CO4 |
√ |
√ |
||||||||||
|
CO5 |
√ |
√ |
||||||||||
|
CO6 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to network simulation tools, Introduction to different types of network cables |
CO1, CO5, CO6 |
|
2. |
Configure Application layer services |
CO2, CO6 |
|
3. |
Basic Router and Switch Configuration, Routing protocol configuration, Network Address translation |
CO2, CO4, CO6 |
|
4. |
Subnetting, VLSM, and IPv6 |
CO2, CO4, CO6 |
|
5. |
Access control lists |
CO3, CO6 |
|
6. |
Wireless router configuration |
CO3, CO4, CO6 |
|
7. |
Implement a custom topology |
CO4, CO6 |
Text Books, Reference Books and Other Resources:
- Computer Networking: A Top-Down Approach---- (James F. Kurose, Keith W. Ross)
-- Instructor contents and PPT slides: http://gaia.cs.umass.edu/kurose_ross/instructor.php
- Cisco Packet Tracer Simulation
- Additional contents: Cisco PowerPoint slides, pdf tutorials will be provided.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C1 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO2 |
PO1, PO2 |
C2 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO3 |
PO2, PO5, PO8 |
C2, A3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO4 |
PO2, PO5 |
C3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO5 |
PO1, PO5 |
P3 |
Demonstration, discussion, experiment |
Quiz/Written Exam, Performance |
|
CO6 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Theory of Computation |
|
Course Code: CSE 309 |
|
Credits: 2 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: DM |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Theory of computation lays a strong foundation for abstract areas in computer science. Theory of computation teaches the learners about the elementary ways in which a computer can be made to think, how efficiently problems can be solved on a model of computation, using an algorithm, tends to set the foundation for understanding Compilers and interpreters.
Course Objectives:
The objectives of this course are:
- To identify with the fundamental limits on what can be efficiently computed in our universe and other possible universes.
- To analyze limits to reveal deep and mysterious properties about information, knowledge and processing, as well as practical issues about what can and cannot be computed.
- To design & build models for complex computation.
Course Outcomes (COs):
After successful completion of this course, students will be able to:
|
CO1 |
Comprehend (C2) formal reasoning about languages. |
|
CO2 |
Categorize (C4) types of different computing languages. |
|
CO3 |
Investigate (C4) advanced knowledge of formal computation and its relationship to languages. |
|
CO4 |
Illustrate (C2) a competent understanding of the concepts of complexity theory. |
Mapping, of Course Learning Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1 |
Language theory, Regular Language: Deterministic and nondeterministic finite automata and their equivalence, conversion of deterministic and nondeterministic finite automata |
CO1 |
|
2 |
Equivalence with regular expressions, Closure properties, The pumping lemma and applications, pushdown automata |
CO2 |
|
3 |
Context-free Grammars and Languages: Definitions, Parse trees, Ambiguous Grammar |
CO2 |
|
4 |
Turing Machines: basic machines, configuration, computing with Turing machines, combining Turing machines |
CO3 |
|
5 |
The pumping lemma for CFLs and applications, Chomsky Normal forms |
CO3 |
|
6 |
General parsing, Sketch of equivalence with pushdown automata. |
CO4 |
|
7 |
Decidability: The undecidability of the halting problem. Reductions to other problems |
CO4 |
Text Books, Reference Books and Other Resources:
- Michael Sipser: Introduction to the Theory of Computation
- Jeffrey Ullman, John Hopcroft, Rajeev Motwani: Introduction to Automata Theory, Languages, and Computation
- Anil Maheshwari, Michiel Smid: Introduction to Theory of Computation
Mapping CO with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Practical Implementation |
Class Test, Assignment Midterm, Final Exam |
|
CO2 |
PO1, PO2 |
C4 |
Lecture, Practical Implementation |
Class Test, Assignment Midterm, Final Exam |
|
CO3 |
PO2, PO4 |
C4 |
Lecture, Practical Implementation |
Class Test, Assignment Midterm, Final Exam |
|
CO4 |
PO1, PO2 |
C2 |
Lecture, Practical Implementation |
Class Test, Assignment Midterm, Final Exam |
|
Course Title: Network and Computer Security |
|
Course Code: CSE 437 |
|
|
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: CN |
|
CIE Marks: 60 SEE- Marks: 40 |
Course Rationale:
This course is meant to offer Computer Science undergraduate students a broad overview of the field of computer security. Students will learn the basic concepts in computer security including software vulnerability analysis and defense, networking and wireless security, and applied cryptography. Students will also learn the fundamental methodology for how to design and analyze security critical systems.
Course Objectives:
- The course covers principles of computer systems and network security.
- We will discuss various attack techniques and how to defend against them.
- Topics include network attacks and defenses, web security, e-mail, malware, mobile security and privacy.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Elaborate (C2) the concepts, issues, principles and theories of computer, web, and Internet security |
|
CO2 |
Apply (C3) and explain (A3) a range of computer network security technologies and tools and services in critical situations |
|
CO3 |
Analyze (C4) solutions to security challenges using common network security tools and formal methods. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
√ |
√ |
||||||||
|
CO3 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Principle of Security, Security goals, Integer Algorithms, Modular Arithmetic and Linear Congruence |
CO1 |
|
2. |
Cryptography (Symmetric key cryptography): Data Encryption Standard (DES), Advanced Encryption Standard (AES) |
CO1, CO2, CO3 |
|
3. |
Cryptography (Asymmetric key cryptography): RSA, Diffie Helman |
CO2, CO3 |
|
4. |
Cryptosystems: ElGamal and Rabin’s Cryptosystems |
CO2, CO3 |
|
5. |
Authentication, Digital Signatures, Digital Signature Standard (DSS), Randomized Encryption; Rabin and ElGamal signature schemes, Cryptographically Secure Hashing; Message Authentication Codes |
CO2, CO3 |
|
6. |
Web/Network security: IPSec, SSL/TLS, Kerberos, PGP, Packet-Filter Firewall, Proxy Firewall, System Security Issues: Malware Analysis. |
CO2, CO3 |
|
7. |
Different types of web vulnerabilities, Introduction to digital forensics concepts, Security in mobile platform, mobile threats and malware. |
CO2, CO3 |
Text Books, Reference Books and Other Resources:
- Behrouz A Forouzan: Cryptography and Network Security
- Contemporary Reference books/materials.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lectures notes, PPT slides, Practice Problems, Video |
Assignment, Class Test, Midterm, Final Exam |
|
CO2 |
PO1, PO2, PO5, PO8 |
C3, A3 |
Lectures notes, PPT slides, Practice Problems, Video |
Assignment, Class Test, Midterm, Final Exam |
|
CO3 |
PO2, PO4, PO5 |
C4 |
Lectures notes, PPT slides, Practice Problems, Software, Video |
Assignment, Class Test, Midterm, Final Exam |
|
Course Title: Neural Network & Fuzzy Logic |
|
Course Code: CSE 451 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: SP |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course tends to help the learners to gain knowledge about design and working principle of artificial neural network and its relation to biological neuron. It helps to develop and design different neuron models according to problem, introduces artificial intelligence and its application areas, application and evaluation of fuzzy logic and fuzzy set theories.
Course Objectives:
The objectives of this course are:
- Facilitating necessary knowledge about the design and working principle of Artificial Neural Networks (ANN) and Deep Learning (DL).
- Teaching the students how the mathematics behind Neural Networks (NN) Learning actually works, rather than presenting only a cursory or surface-level description.
- Helping the students conceptualize and understand the key parameters in a neural network's architecture and apply them to their own applications.
- Gaining the basics of different application areas and evaluation of fuzzy logic and fuzzy set theories.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Illustrate (C3) how different components are combined to form a Single-layer (Perceptron) and Multi-layer NN and their basic working mechanism. |
|
CO2 |
Use (C3) the knowledge about the principle and mathematics behind the Training of a simple NN (Loss/Cost Function, Gradient Descent, Computation Graph). |
|
CO3 |
Explain (C2) fuzzy systems' fundamental concepts (fuzzy number, fuzzy relation, composition of fuzzy relation). |
|
CO4 |
Implement (C3) a fuzzy system representing uncertain knowledge using fuzzy rules. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
A Gentle Introduction to NN: Differences among AI/ML/DL, Subcategories of ML and their working principle, Decision Boundary, Classification Example: AND, OR, XOR, Biological Vs. Artificial NN |
CO1 |
|
2. |
Applications of Neural Network: An abstract example of NN, Supervised Learning with NN, Popular NN Architectures (ANN, CNN, RNN, Transformers), Reason behind Deep Learning's success |
CO1 |
|
3. |
Structural Building Blocks of NN: Input/Output Layers, Weights and Bias, Activation Function (non-linearity), Summation Vs. Matrix. |
CO2 |
|
4. |
Single Layer Perceptron (A Simple NN): Linear Regression, Training set, Input/Output, Forward Propagation, Pitfall of Single Layer Perceptron. |
CO2 |
|
5. |
Multi-Layer NN: Concepts of Hidden Layer, XOR Calculation Using Summation Formula, ReLU Activation Function, Vectorized Representation of Multi-Layer NN, Adding Bias as a weight. |
CO2 |
|
6. |
How NN's Learns: Weight Initialization (Random vs. Zero), Expected Vs Predicted Output, Loss and Cost Function, Back-propagation Basics. |
CO3 |
|
7. |
Logistic Regression (LR): The pitfalls of Linear Regression, Binary Classification, From Linear to Logistic Regression, Sigmoid Activation Function. |
CO1 |
|
8. |
Loss and Cost Function: Training/Dev/Test set, Loss function: M.S.E, Convex Vs. Non-convex, Local Vs. Global Optima, Log/Cross-Entropy Loss., L1 and L2 M.A.E, Cost Function, SoftMax Activation Function. |
CO3 |
|
9. |
Gradient Descent (G.D): Finding the Global Optima, Derivatives, Weights and Bias Update, Learning Rate, and Computation Graph. |
CO3 |
|
10. |
Backward Propagation: Back-prop using Computation Graph, G.D with Backpropagation for LR, G.D with ‘M’ training examples, G.D Algorithm using Summation, Vectorized G.D, Updating Weights and Bias, Iteration Vs. Batch Vs. Epochs. |
CO3 |
|
11. |
Introduction to Fuzzy Logic: Fuzzy Set, Fuzzy Set Operations - Union, Intersection, Complement, Properties of Fuzzy Set, Extension Principles, Alfa-cuts. |
CO4 |
|
12. |
Fuzzy Relations: Properties, Basic Operations, Compositions of Fuzzy Relations. |
CO4 |
|
13. |
Fuzzy Number: Representation, Properties, Addition, Subtraction of Discrete and Continuous Fuzzy Number, Addition and Subtraction of Discrete Fuzzy Number through Extension Principle, Multiplication and Division of Fuzzy Number. |
CO4 |
|
14. |
Fuzzy Linguistic Description: Linguistic Variables and Values, Implication Relations, Fuzzy Inference, and Composition. |
CO4 |
Text Books, Reference Books and Other Resources:
- Dive into Deep Learning – By Amazon Research Scientists.
- "Make Your Own Neural Network" – By Tariq Rashid
- "Fundamentals of Deep Learning", O’Reilly – By Nikhil Buduma.
- "Deep learning" – By Ian Goodfellow and Yoshua Bengio and Aaron Courville.
- Neural Networks and Deep Learning – By Michael Nielsen.
- "Fuzzy and Neural Approach in Engineering" – Lefteri H. Tsoukalas, Robert E. Uhrig.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C3 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1, PO2 |
C2 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
CO4 |
PO1, PO2, PO4 |
C3 |
Lecture, Problem solution, Video, Web Link |
Class Test, Assignment, Midterm, Final Exam |
|
Course Title: Neural Network & Fuzzy Logic Laboratory |
|
Course Code: CSE 452 |
|
Credits: 1 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: SPL |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
This subject aims to gain knowledge about design and working principle of neural network (NN) as well as practically implement NN for real-world applications.
Course Objectives:
The objectives of the course are:
- To teach students the foundations of implementing NN’s using modern tools and libraries.
- To disseminate the knowledge of how to appropriately report on the experiments they run, as done in academic publications.
Course Outcomes:
Upon successful completion of this course, students will be able to
|
CO1 |
· Use (C3) proper environment and software packages necessary for preprocessing, developing, and analyzing the performance of neural network. |
|
CO2 |
Build (C3) a NN using modern software tools and extend it by adding multiple layers to it to understand how Multi-layer NN works. |
|
CO3 |
· Investigate (C4) the results of a neural network. |
|
CO4 |
· Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
√ |
√ |
√ |
|||||||
|
CO3 |
√ |
√ |
√ |
√ |
√ |
|||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Environment Setup: General Issues, Setting-up Anaconda/CoLab, Recap of Python Containers and Collection Modules, NumPy Basics. |
CO1, CO4 |
|
2. |
Introduction to the different data sources, reading, preprocessing, and splitting the data into training and test set |
CO1, CO2, CO4 |
|
3. |
Building A Simple NN using latest frameworks. Compiling Multi-Layer NN and Parameter/Hyper Parameter Tuning, Regression using Neural Networks, Classification using Neural Networks, plotting loss and accuracy curve of training and validation set, Performance Measure |
CO1 - CO4 |
Text Books, Reference Books and Other Resources:
- "Deep Learning with Python" – By Francois Chollet
- "Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow", O’Reilly, 2nd Ed. (2019) – By Aurélien Géron
- "Deep Learning from Scratch: Building with Python from First Principles" – By Seth Weidma
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO5 |
C3 |
Lecture, Lab Task |
Project, Presentation, Assignment, Lab Performance, Viva |
|
CO2 |
PO1, PO2, PO3, PO5, PO9 |
C3 |
Lecture, Lab Task |
Project, Presentation, Assignment, Lab Performance, Viva |
|
CO3 |
PO1, PO2, PO3, PO4, PO9 |
C4 |
Lecture, Lab Task |
Project, Presentation, Assignment, Lab Performance, Viva |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Computer Graphics & Image Processing |
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Course Code: CSE 455 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: SP |
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CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Computer graphics concentrates on the fundamentals of computer graphics and addresses the knowledge and skill in computer graphics development which are essential for computing professionals. Image processing, on the other hand emphasizes on general principles of image processing and its application.
Course Objectives:
The objectives of this course are:
- To develop a theoretical foundation of fundamental computer Graphics & Digital Image Processing concepts.
- To learn basic algorithms for computer graphics and image processing.
- To understand and imply various filters, Point processing, and Arithmetic operations in image processing.
- To understand different applications of graphics and image processing.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Explain (C2) the fundamental concepts of computer graphics and image processing. |
|
CO2 |
Demonstrate (C3) the scan conversion algorithms for drawing various types of geometric shapes. |
|
CO3 |
Illustrate (C3) the ideas of 2D and 3D transformation and clipping techniques. |
|
CO4 |
Use (C3) different types of image processing techniques for transformation, filtering, smoothing and enhancement. |
|
CO5 |
Solve (C3) different image compression algorithms, segmentation and feature extraction techniques. |
Mapping of Course Outcomes to Program Outcomes:
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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CO2 |
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√ |
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CO3 |
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CO4 |
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CO5 |
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Course Description:
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SL No. |
Course Content |
COs |
|
1. |
Fundamental Concepts: Image representation, color model, pixel, rasterization, lookup table, image types, graphical hardware, image fundamentals, sampling, quantization, mathematical tools. |
CO1 |
|
2. |
Scan conversion: Scan conversion algorithms for point, line, circle, ellipse, rectangle, Region filling, scan converting character, anti-aliasing |
CO2 |
|
3. |
2D and 3D Transformation, viewing, clipping: Geometric transformation, translation, rotation, scaling, mirror reflection, co-ordinate transformation, composite transformation, instance transformation, viewport mapping, shape clipping, clipping algorithms, curves |
CO3 |
|
4. |
Image processing: Fundamental concepts, color model conversion, smoothing, filtering, sharpening, fourier transformation, image enhancement, image restoration. |
CO1, CO4 |
|
5. |
Compression and segmentation: Huffman coding, Arithmetic coding, LZW coding, Bit-plane coding, Wavelet coding, watermarking, thresholding, segmentation, feature extraction. |
CO5 |
Text Books, Reference Books and Other Resources:
- Computer Graphics: Zhigang Xiang and Roy Plastock
- Digital Image Processing: Rafael C. Gonzalez, Richard E. Woods
- Computer Graphics: Principles and Practice: James D Foley, Andries Van Dan
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Slide |
Class Test, Assignment, Midterm, Final |
|
CO2 |
PO1, PO2 |
C3 |
Lecture, Slide |
Class Test, Assignment, Midterm, Final |
|
CO3 |
PO1, PO2 |
C3 |
Lecture, Slide |
Class Test, Assignment, Midterm, Final |
|
CO4 |
PO1, PO2 |
C3 |
Lecture, Slide |
Class Test, Assignment, Midterm, Final |
|
CO5 |
PO1, PO2 |
C3 |
Lecture, Slide |
Class Test, Assignment, Midterm, Final |
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Course Title: Computer Graphics & Image Processing Laboratory |
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Course Code: CSE 456 |
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Credits: 1 Class Hours/Week: 2 |
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Course Type: Core Pre-requisite: SPL |
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CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
In Computer Graphics & Image Processing Laboratory course, the students will learn various computer graphics algorithms. In this program, the students will have to implement the mostly used computer graphics algorithms like line drawing, polygon clipping, line clipping etc. For the image processing part, students will learn about different color models and conversion among them. In this part, binary image manipulation will be performed.
Course Objectives:
The objective of the course is to enable the students to
- Contribute effectively in the research area of computer graphics and image processing.
- Students will learn about the practical use of various computer graphics and image processing algorithms.
- Students will be able to implement new algorithms to overcome the existing problems.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Implement (C3) various scan conversion algorithms using available graphical tools. |
|
CO2 |
Execute (C3) various graphical transformation methods. |
|
CO3 |
Implement (C3) various image processing techniques. |
|
CO4 |
Demonstrate (C3) the skills of computer graphics and image processing to develop a mini project. |
|
CO5 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
✓ |
✓ |
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CO2 |
✓ |
✓ |
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CO3 |
✓ |
✓ |
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CO4 |
✓ |
✓ |
✓ |
✓ |
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CO5 |
✓ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Scan Conversion Algorithm: Digital Differential Analyzer Algorithm, Bresenham Line Drawing Algorithm, Midpoint Circle Drawing Algorithm. |
CO1, CO5 |
|
2. |
Transformation: Geometric transformation, translation, rotation, window to viewport mapping. |
CO2, CO5 |
|
3. |
Image Processing: Color model, Binary image analysis, Image restoration techniques. |
CO3, CO5 |
|
4. |
Mini Project Development: Unity, OpenGL or any other platforms/tools. |
CO4, CO5 |
Text Books, Reference Books and Other Resources:
- Computer Graphics (Second Edition): Zhigang Xiang
- Digital Image Processing: Rafael C. Gonzalez, Richard E. Woods
- Computer Graphics: Principles and Practice: James D Foley, Andries Van Dan
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO5 |
C3 |
Lecture, Slide |
Performance, Assignment |
|
CO2 |
PO1, PO5 |
C3 |
Lecture, Slide |
Performance, Assignment |
|
CO3 |
PO1, PO5 |
C3 |
Lecture, Slide |
Performance, Assignment |
|
CO4 |
PO1, PO2, PO3, PO5 |
C3 |
Lecture, Slide |
Performance, Assignment |
|
CO5 |
PO10 |
A3 |
Demonstration |
Report |
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Course Title: Control Systems |
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Course Code: EEE 313 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: SS |
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CIE Marks: 60 SEE Marks: 40 |
Course Rationale: This course aims to provide basic knowledge of different control techniques used in industries to control electrical and mechanical devices.
Course Objectives:
The objectives of this course are to:
- Acquaint students with the basic knowledge of modern control systems.
- Help the students develop their ability in developing mathematical models of electrical system.
- Get idea about the principle of block diagram reduction and signal flow graphs.
- Provide knowledge of the stability of electrical and mechanical systems.
- Help them conceptualize the basic theories of the system analysis technique.
- Make the students understand the basic knowledge of different types of controllers.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Describe (C2) the fundamentals of control systems. |
|
CO2 |
Construct (C4, A4) mathematical models of different Control systems satisfying desirable control objectives. |
|
CO3 |
Investigate (C4) different control systems using block diagrams and signal flow graphs. |
|
CO4 |
Design (C4) different control systems using classical approaches and modern techniques. |
|
CO5 |
Inspect (C4) system stability. |
|
CO6 |
Explain (C1) the basics of nonlinear control. |
Mapping of Course Outcomes to Program Outcomes:
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PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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CO1 |
√ |
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CO2 |
√ |
√ |
√ |
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CO3 |
√ |
√ |
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CO4 |
√ |
√ |
√ |
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CO5 |
√ |
√ |
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CO6 |
√ |
Course Description:
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SL No. |
Course Content |
COs |
|
1. |
Introduction: Introduction to the control system, open loop and closed loop systems, the design process. |
CO1 |
|
2. |
Mathematical Model: Review of Laplace transform, initial and final value theorems, transfer functions: Open-loop stability, Poles Zeros state, space representation/transfer function/zero-pole of control system design; state space representation; solution of state equation. |
CO2 |
|
3. |
Block diagram approach: Signal flow graph; block diagram theory; block diagram reduction method; |
CO3 |
|
4. |
Classical Control System: Phase lead and lag controllers, Linear control system design using state feedback, Closed-loop sensitivity functions, LQR design, pole placement, lead compensation, lag compensation, lead-lag compensation. |
CO4 |
|
5. |
Modern Control System: Application of Eigen value and Eigen vectors, state variable analysis, canonical forms, controllability and observability, controller, and observer design, Riccati equation, data driven control basics. |
CO4 |
|
6. |
Stability analysis: Analysis methods such as Nyquist stability criterion, root locus, routh's criteria, Stability margins, gain and phase margin, maximum magnitude, resonant frequency. |
CO5 |
|
7. |
Controller Design: P, I, PI, PD, and PID types, optimum controller design, robust controller design. |
CO2 |
|
8. |
Non-linear control: Introduction to nonlinear control, Lyapunov stability criteria. Introduction to neural and fuzzy control. |
CO6 |
Textbooks, References and Other Resources:
- Control Systems Engineering by Norman S. Nise
- Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control by J. Nathan Kutz and Steven L. Brunton
- Linear control system analysis and Design, John J. Azzo
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2, PO3 |
C4, A4 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C4 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO4 |
PO1, PO2, PO3 |
C4 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO5 |
PO2, PO3 |
C4 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
CO6 |
PO1 |
C1 |
Lecture, Slide, Problem Solving, and examples |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Control Systems Laboratory |
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Course Code: EEE 314 |
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Credits: 1.5 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: SSL |
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CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
This course aims to build foundation skills on designing and analyzing different industrial control systems using PLC and MATLAB.
Course Objectives:
The objectives of this course are to:
- Help students demonstrate the controlling of systems using PLC
- Improve the ability to present the results of investigations.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Implement (C3, P2) ladder diagram for PLC based automation system and design the best controller based on the systems requirement using CAD tool as an individual or as a member of a team. |
|
CO2 |
Evaluate (C4) the results from experimental data. |
|
CO3 |
Write (A3) comprehensive reports on the work done in laboratory. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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|
CO1 |
√ |
√ |
√ |
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|
CO2 |
√ |
√ |
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|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Laboratory work based on theory course EEE 313. It will cover hardware-based work in PLC system. |
CO1 |
|
2. |
Report writing based on laboratory work. |
CO2 |
|
3. |
Presentation on mini project work. |
CO3 |
Text Books, Reference Books and Other Resources:
- Lab manual
CO Delivery and Assessment:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C3, P2 |
Lecture, Slide, Problem Solving, and examples |
Performance, Assignment, Quiz, Viva |
|
CO2 |
PO2, PO4 |
C4 |
Lecture, Slide, Problem Solving, and examples |
Performance, Assignment, Quiz, Viva |
|
CO3 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Thesis/Project |
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Course Code: CSE 400 |
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Credits: 4 Class Hours/Week: 4 |
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Course Type: Core Pre-requisite: As Set by Supervisor |
Course Rationale:
This course introduces students to computer science and engineering research through planning and managing an innovative capstone research project, using research methods, and considering broader professional issues related to the project.
Course Objectives:
The objectives of the course are to:
- Provide an opportunity to integrate and apply their previous engineering knowledge acquired throughout their undergraduate program to the solution of complex computing problems.
- Develop creativity in analyzing and solving complex and possibly real-world or industry-related computing problems.
- Develop skills to systematically design, develop, and document the solution of research projects.
- Develop and enhance self-learning and life-long learning capabilities.
- Make students aware of professional and ethical norms, conducts, and responsibilities in designing solutions to computing problems.
- Facilitate modern software and engineering tools necessary to meet customer requirements.
- Build the capacities needed to plan and manage a real-time project.
- Gauge the impact of an engineering solution on the community, cultural context, physical and mental health, safety and security, environment, and sustainability.
- Promote teamwork to solve real-world problems.
- Develop written and verbal communication skills among students to communicate to a
variety of audiences.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Plan (C6, A3) a project considering the social, cultural, global, health, and environmental responsibilities of the professional Engineer and the principles of sustainable design and development of national and international perspective |
|
CO2 |
Apply (C3, P3, A3) modern tools and techniques to manage projects under commitment to professional and ethical responsibilities |
|
CO3 |
Develop (A3) the ability to communicate effectively, not only with engineers but also with the community at large as an individual and in multi-disciplinary and multi-cultural teams |
|
CO4 |
Apply (C4, A4) robust project risk identification, feasibility test, assessment and treatment process |
|
CO5 |
Develop (C4, A3) the capacity to undertake lifelong learning by analyzing real world situations |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
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|
CO1 |
√ |
√ |
√ |
√ |
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CO2 |
√ |
√ |
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|
CO3 |
√ |
√ |
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|
CO4 |
√ |
√ |
√ |
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|
CO5 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1 |
The Capstone Project enables students to practice what they've learned in previous courses to the solution of a real-world computing problem. The types of research projects may include research-intensive, design, and development of a product or software or system, and solution to an engineering problem for an industry partner. The research will contribute new knowledge to the relevant field and achieve social, economic, environmental, and cultural outcomes. Students will work independently and or in a group under the guidance of a supervisor to carry out different tasks needed to solve problems and design solutions. |
CO1, CO2, CO3, CO4, CO5
|
Textbooks, Reference Books and Other Resources:
- World-wide web
- ACM Digital Library
- Digital Contents
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO2, PO3, PO6, PO7 |
C6, A3 |
Weekly meeting in-person or virtual, Web links, Reference material |
Performance, Report, and Presentation |
|
CO2 |
PO5, PO8 |
C3, P3, A3 |
||
|
CO3 |
PO9, PO10 |
A3 |
||
|
CO4 |
PO3, PO4, PO11 |
C4, A4 |
||
|
CO5 |
PO12 |
C4, A3 |
Weekly meeting in-person or virtual, Web links, Reference material |
Performance, Report, and Presentation |
|
Course Title: Compiler Construction |
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Course Code: CSE 453 |
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Credits: 3 Class Hours/Week: 3 |
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Course Type: Core Pre-requisite: ToC |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
Intended to enable the students the basic techniques which underlie the practice of compiler construction and use the acquired knowledge to build a compiler for a language.
Course Objectives:
The objectives of this course are to:
- To introduce the major concept areas of language translation and compiler design.
- Provide the foundation for understanding the theory and practice of compilers.
- To learn programming language translation and compiler design concepts, language recognition,
symbol table management, semantic analysis and code generation. - To provide practical programming skills necessary for constructing a compiler.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Describe (C2) the basic concepts, principles, tools, and techniques of a compiler construction. |
|
CO2 |
Apply (C3) the knowledge of different phases of a compiler to undertake language translation. |
|
CO3 |
Evaluate (C5) the similarities and differences among various parsing techniques and grammar transformation techniques. |
|
CO4 |
Construct (C3) context-free grammar and regular expressions to implement lexical syntactic and semantic structures. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to compilers: Introductory concepts, Types, Applications, Phases, compiler construction tools |
CO1 |
|
2. |
Syntax directed translation: Construction of syntax trees, Top down translation Parser and its role, Context free grammars, Syntax analysis |
CO1 |
|
3. |
Lexical analysis: Role of the lexical analyzer, Token specification, Recognition of tokens, Symbol table, Finite automata |
CO2, CO4 |
|
4. |
Context free grammar: Syntax error handling, Ambiguity, left recursion, Left factoring, Different types of parser. |
CO3, CO4 |
|
5. |
Intermediate code generator: DAG, three address code, code generation, Addressing mode, instruction cost, basic block, Flow graph. |
CO2, CO3 |
|
6. |
Code optimization: Basic concepts, Code optimization techniques |
CO2 |
|
7. |
Syntax directed translation: Syntax directed definition, Semantic rules analysis, Dependency graph, Annotated parse tree, implementation of SDT |
CO1 |
Text Books, Reference Books and Other Resources:
- Aho, Ulman & Ravishethi: Principal of Compiler Design.
- Philip: Compiler Design Theory.
- Willam A. Barrette: Compiler Construction, Theory and Design.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture notes, Slide |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1 |
C3 |
Lecture notes, Slide |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO2, PO4 |
C5 |
Lectures notes, Slide |
Class Test, Midterm, Assignment, Final Exam |
|
CO4 |
PO1, PO2 |
C3 |
Lectures notes, Slide |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Compiler Construction Laboratory |
|
Course Code: CSE 454 |
|
Credits: 1.5 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: ToC |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
Intended to enable the students the basic techniques which underlie the practice of compiler construction and use the acquired knowledge to build a compiler for a language.
Course Objectives:
The objectives of this course are:
- To introduce the major concept areas of language translation and compiler design.
- Provide the foundation for understanding the theory and practice of compilers.
- To learn programming language translation and compiler design concepts, language recognition, symbol table management, semantic analysis and code generation.
- To provide practical programming skills necessary for constructing a compiler.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Apply (C3) software tools and techniques to construct compiler |
|
CO2 |
Apply (C3) syntax analyzer, parser, semantic analyzer and various parsing techniques in Compiler Design |
|
CO3 |
Apply (C3) mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems. |
|
CO4 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
√ |
|||||||||
|
CO3 |
√ |
√ |
√ |
|||||||||
|
CO4 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Laboratory work based on theory course Compiler Construction |
CO1, CO2, CO3 |
|
2. |
Report generation based on Lab work |
CO4 |
Text Books, Reference Books and Other Resources:
- Aho, Ulman & Ravishethi: Principal of Compiler Design.
- Philip: Compiler Design Theory.
- Willam A. Barrette: Compiler Construction, Theory and Design
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO5 |
C3 |
Problem analysis, Demonstration, Problem solving |
Performance, Report, Quiz |
|
CO2 |
PO1, PO2, PO5 |
C3 |
Problem analysis, Demonstration, Problem solving |
Performance, Quiz, Report |
|
CO3 |
PO1, PO2, PO5 |
C3 |
Problem analysis, Demonstration, Problem solving |
Performance, Quiz, Report |
|
CO4 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Machine Learning |
|
Course Code: CSE 457 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: AI |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course provides appropriate machine learning techniques, and learning algorithm to best suit the current need and enhance the learning parameters for maximum performance.
Course Objectives:
- Providing the students with an in-depth introduction to two main areas of Machine Learning: supervised and unsupervised
- Introducing some of the main models and algorithms for regression, classification, and clustering
- Developing an understanding of the theoretical relationships between the learning algorithms
- Enhancing the learning parameters to achieve maximum performance
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) the key concepts such as supervised learning, unsupervised learning, reinforcement learning, feature engineering, model evaluation, and trade-off bias and variance. |
|
CO2 |
Apply (C3) supervised learning, unsupervised learning and reinforcement learning algorithms to datasets. |
|
CO3 |
Analyze (C4) data for preprocessing and cleaning datasets to prepare them for machine learning tasks, gain insights and identify patterns in the data. |
|
CO4 |
Evaluate (C5) and optimize the performance of machine learning models using model selection, hyperparameter tuning, model validation, and metrics such as accuracy, precision, recall, F1 score, and area under the curve (AUC). |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
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|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Machine Learning: Classification of learning, Unsupervised and supervised learning |
CO1, CO2 |
|
2. |
Linear Regression with One Variable: application of linear regression, cost function, and gradient descent method for learning |
CO2, CO3, CO4 |
|
3. |
Linear Regression with Multiple Variables, Logistic Regression, and Regularization; |
CO2, CO3, CO4 |
|
4. |
Neural Networks: Representation, Learning, Multilayer feed forward network, Back propagation algorithm for training a feed forward network |
CO2, CO3, CO4 |
|
5. |
Applications: Advice for Applying Machine Learning, Machine Learning System Design, Support Vector Machines |
CO3, CO4 |
Text Books, Reference Books and Other Resources:
- Pattern Recognition and Machine Learning by Christopher M. Bishop
- Machine Learning: A Probabilistic Perspective, by Kevin Murphy.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture, Problem solution, Video, Web Link |
Class test, Midterm, Assignment, Final |
|
CO2 |
PO1, PO2 |
C3 |
Lecture, Problem solution, Video, Web Link |
Class test, Midterm, Assignment, Final |
|
CO3 |
PO2, PO4 |
C4 |
Lecture, Problem solution, Video, Web Link |
Class test, Midterm, Assignment, Final |
|
CO4 |
PO2, PO4 |
C5 |
Lecture, Problem solution, Video, Web Link |
Class test, Midterm, Assignment, Final |
|
Course Title: Machine Learning Laboratory |
|
Course Code: CSE 458 |
|
Credits: 1 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: AIL |
|
CIE Marks: 40 SEE Marks: 60 |
Course Rationale:
This subject provides most effective machine learning techniques, learning algorithm to best suit the current need and enhance the learning parameters for maximum performance.
Course Objectives:
The objectives of the course are:
- To provide students with an in-depth introduction to two main areas of Machine Learning: supervised and unsupervised.
- To apply some of the main models and algorithms for regression, classification, and clustering.
- To enhance the learning parameters to achieve maximum performance.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
· Implement (C3) different machine learning algorithms for classification, regression, clustering, and dimensionality reduction using modern tools and libraries such as scikit-learn, TensorFlow and/or PyTorch etc. |
|
CO2 |
Apply (C3) appropriate methods for handling missing data and dealing with class imbalance using the above stated tools |
|
CO3 |
Apply (C3) appropriate mitigation techniques to solve the issues of overfitting, underfitting, bias, and variance in machine learning models using the same tools |
|
CO4 |
Evaluate (C5) the performance of different machine learning algorithms using cross-validation and other validation techniques using the mentioned tools |
|
CO5 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
√ |
|||||||||
|
CO2 |
√ |
√ |
√ |
|||||||||
|
CO3 |
√ |
√ |
√ |
|||||||||
|
CO4 |
√ |
√ |
√ |
√ |
||||||||
|
CO5 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Data Preprocessing, Regression, SVM, KNN, Decision Tree, Naïve Bayes classification, K-Means Clustering |
CO1 – CO4 |
|
2. |
Association Rule Learning: Apriori, Eclat, PCA, Model Selection and Boosting |
CO1 – CO4 |
|
3. |
Report preparation based on lab work |
CO5 |
Text and Reference books:
- Introduction to Machine Learning with Python: A Guide for Data Scientists - Andreas C. Müller, Sarah Guido
- Machine Learning in Action - Peter Harrington
- Python Machine Learning - By Sebastian Raschka
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Performance, Assignment, Report |
|
CO2 |
PO1, PO2, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Performance, Assignment, Report |
|
CO3 |
PO1, PO2, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Performance, Assignment, Report |
|
CO4 |
PO1, PO2, PO4, PO5 |
C5 |
Demonstration, Discussion, Experiment |
Performance, Assignment, Report |
|
CO5 |
PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Pattern Recognition |
|
Course Code: CSE 459 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: AI |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course will study state-of-the-art techniques for analyzing data. The goal is to extract meaningful information from feature data. This includes statistical and information theoretic concepts relating to machine learning, data mining and pattern recognition.
Course Objectives:
The main objectives of this course are:
- The students should have a clear understanding of the design and construction and a pattern recognition system.
- To introduce the major approaches of pattern recognition.
- Finally, the student will have a clear working knowledge of implementing pattern recognition techniques.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
|
CO1 |
Demonstrate (C2) the essential principles, theories, and techniques underlying pattern recognition: statistical modeling, machine learning algorithms, and data analysis methods. |
|
CO2 |
Implement (C3) pattern recognition systems considering data preprocessing, extract relevant features, and train models using various algorithms. |
|
CO3 |
Apply (C3) pattern recognition algorithms and tools to real-world problems: computer vision, speech recognition, natural language processing, and bioinformatics. |
|
CO4 |
Assess (C5) the performance of pattern recognition algorithms using appropriate evaluation metrics. |
|
CO5` |
Comprehend (C2) the ethical and social implications of pattern recognition such as privacy, bias, and fairness. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
||||||||||
|
CO5 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Definitions, Datasets for Pattern Recognition, Different Paradigms of Pattern Recognition and Machine Learning, Data Normalization, Hypothesis Evaluation, VC-Dimensions and Distribution, Bias - Variance Tradeoff, Regression (Linear) |
CO1 |
|
2. |
Feature Selection and Dimensionality Reduction: PCA, LDA, ICA, SFFS, SBFS Additional Features and Template Matching: Texture, Shape and Size Characterization, Fractals, Features for Audio |
CO2 |
|
3. |
Discriminative Methods: Distance-based methods, Linear Discriminant Functions, Decision Tree, Random Decision Forest and Boosting. Bayes Decision Theory: Bayes decision rule, Minimum error rate classification, Normal density and discriminant functions, Bayesian networks Parameter Estimation: Maximum Likelihood and Bayesian Parameter Estimation Artificial Neural Networks: MLP and Backpropagation Kernel Machines: Kernel Tricks, Support Vector Machines Clustering: k-means clustering, Gaussian Mixture Modeling |
CO3 |
|
4. |
Confusion Matrix in Machine learning, Receiver Operating Characteristic (ROC) Curve |
CO4 |
|
5. |
Legal and Ethical consideration in pattern recognition |
CO5 |
Text and Reference Books:
- Duda, R.O., Hart, P.E., and Stork, D.G. (2001), Pattern Classification. Wiley-Interscience. (2nd Edition)
- Devi V.S.; Murty, M.N. (2011), Pattern Recognition: An Introduction, Universities Press, Hyderabad.
- I. Kuncheva (2004.), Combining Pattern Classifiers: Methods and Algorithms, Wiley-Blackwell
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO4 |
PO2, PO4 |
C5 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO5 |
PO4, PO6, PO8 |
C2 |
Lecture notes, PPT slides, problem solving, web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Pattern Recognition Laboratory |
|
Course Code: CSE 460 |
|
Credits: 01 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: AIL |
|
CIE Marks: 30 SEE Marks: 70 |
Course Rationale:
This subject aims to practically implement as well analyze the various procedures, methods and algorithms related to pattern recognition for specific application.
Course Objectives:
The objective of the course is to enable the students to
- Have a clear understanding of the design and construction and a pattern recognition system.
- Introduce the students, the major approaches in template and statistical pattern recognition.
- Have a clear working knowledge of implementing pattern recognition techniques and the scientific python computing environment.
Course Outcomes:
Upon successful completion of this course, students will be able to
|
CO1 |
Apply (C3) pattern recognition algorithms to real-world datasets: preprocess data, select appropriate features, train models, and evaluate the performance of the algorithms. |
|
CO2 |
Use (C3) pattern recognition tools and software packages to implement and test different algorithms, analyze the results, and visualize the patterns discovered. |
|
CO3 |
Analyze (C4) complex datasets to extract meaningful insights, identify relevant patterns, and make informed decisions based on the analysis. |
|
CO4 |
Report (A3) project work both written and verbally. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
√ |
|||||||||
|
CO2 |
√ |
√ |
√ |
|||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1 |
Image Manipulation, Enhancement, Filtering, Convolution, Segmentation, Feature Extraction, Feature Selection |
CO1, CO4 |
|
2 |
Supervised classification, Unsupervised clustering, Artificial Neural Network, Convolutional Neural Networks: elements, architectures, convolution visualization; Software Packages and tools: Tensorflow, Keras, Sklearn, NumPy, Matpoltlib |
CO2, CO4 |
|
3 |
Design a project on open-source dataset using state-of-the-art models |
CO3, CO4 |
Text and Reference Books:
- Duda, R.O., Hart, P.E., and Stork, D.G. (2001), Pattern Classification. Wiley Interscience. 2nd Edition.
- Devi V.S.; Murty, M.N. (2011), Pattern Recognition: An Introduction, Universities Press, Hyderabad.
- I. Kuncheva (2004.), Combining Pattern Classifiers: Methods and Algorithms, Wiley-Blackwell
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s taxonomy domain/level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Report, Performance, Presentation, Viva |
|
CO2 |
PO1, PO2, PO5 |
C3 |
Demonstration, Discussion, Experiment |
Report, Performance, Presentation, Viva |
|
CO3 |
PO4, PO5 |
C4 |
Demonstration, Discussion, Experiment |
Report, Performance, Presentation, Viva |
|
CO4 |
PO9, PO10 |
A3 |
Demonstration |
Report |
|
Course Title: Contemporary Courses of Computer Science |
|
Course Code: CSE 481 |
|
Credits: 3 Class Hours/Week: 3 |
|
Course Type: Core Pre-requisite: CN |
|
CIE Marks: 60 SEE Marks: 40 |
Course Rationale:
This course is intended for the students who seek an overall understanding of cloud computing core concepts, architecture, its history, popular cloud services, security, pricing, and the technologies enabled by cloud computing.
Course Objectives:
- Identify and demonstrate different cloud computing and cloud deployment models.
- Comprehend the compute, storage, database, networking, and content delivery facilities offered by the underlying cloud infrastructure.
- Identify security and privacy issues in cloud computing.
- Analyze the automatic scaling and monitoring performance of the underlying cloud technologies
- Implement applications for different cloud platforms.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Define (C1) the key concepts, standards, and technologies in cloud computing. |
|
CO2 |
Describe (C2) the performance, scalability, and availability of the underlying cloud technologies. |
|
CO3 |
Compare (C4) resource usage in cloud computing infrastructures for different scientific applications. |
|
CO4 |
Describe (C2) privacy and security issues for cloud infrastructure and virtual environments. |
|
CO5 |
Design (C6) solutions for complex cloud hosting problems. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
||||||||||
|
CO5 |
√ |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction to Cloud Computing: Grid Computing, Distributed computing, Cloud computing models such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) |
CO1 |
|
2. |
Cloud deployment models: public, private, and hybrid models. Example cloud platforms (e.g. AWS, Google Cloud Platform, Microsoft Azure), and Interoperability. Cloud Economics and Billing: Pricing Fundamentals, Cost of ownership, On-premises vs. Cloud solution, Organizations and Accounts, Billing and Cost management |
CO1 |
|
3. |
Cloud infrastructure: Points of presence, Region, Availability Zones, Data Centers, Edge Locations |
CO1 |
|
4. |
Cloud Security: Shared responsibility in the cloud, Identity and Access Management, Securing Users, Securing Data |
CO4 |
|
5. |
Networking and Content Delivery: Virtual Private Cloud (VPC), VPC networking, VPC sharing, VPC Peering, Site-to-site VPN, VPC Transit Gateway, Connecting on-premises data center to cloud, VPC Security, Routing Tables, Security groups, ACLs, Routing and DNS, Content Delivery Network, Pricing Transit Gateway |
CO2, CO4 |
|
6. |
Compute: EC2, EC2 Cost Optimization, Types of EC2 instances, Container Services, Docker, Serverless Computing: AWS Lamda and Elastic Beanstalk, key management services |
CO3, CO5 |
|
7. |
Cloud Storage: Object Storage, Block Storage, Network File System, Long Term Storage, automatic scaling of storages, Lifecycle management, Types of Object Storage, Use cases of different types of storages |
CO3 |
|
8. |
Cloud Database: Relational/SQL Database, NoSQL databases, Data storage for OLTP systems, warehouse, automatic scaling database systems, Reliability, Availability, Replication. |
CO2 |
|
9. |
Cloud Architecture: Well-Architected Framework, Pillars of the framework, Reliability and Scalability, Cloud Resource Provisioning |
CO2, CO3 |
|
10. |
Load Balancing, Auto Scaling, Dynamic Scaling, Cloud Performance Monitoring |
CO2 |
Text Books, Reference Books and Other Resources:
- AWS Cloud Fundamentals Online Course Material
- Cloud Computing: A Hands-On Approach, by Arshdeep Bahga and Vijay Madisetti.
- Cloud Computing Theory and Practice, by Dan Marinescu, 2nd Edition.
- Cloud Computing: Principles and Paradigms, by Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, 1st Edition, Wiley
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C1 |
Lecture notes, PPT slides, problem solving, AWS web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO2 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides, problem solving, AWS web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO3 |
PO2, PO4 |
C4 |
Lecture notes, PPT slides, problem solving, AWS web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO4 |
PO1, PO2 |
C2 |
Lecture notes, PPT slides, problem solving, AWS web content |
Class Test, Midterm, Assignment, Final Exam |
|
CO5 |
PO3, PO4, PO5 |
C6 |
Lecture notes, PPT slides, problem solving, AWS web content |
Class Test, Midterm, Assignment, Final Exam |
|
Course Title: Contemporary Courses of Computer Science Laboratory |
|
Course Code: CSE 482 |
|
Credits: 1 Class Hours/Week: 2 |
|
Course Type: Core Pre-requisite: CNL |
|
CIE Marks: 70 SEE Marks: 30 |
Course Rationale:
This course enables the students to become familiar with web application implementation and hosting, and service configuration in real-world cloud platforms.
Course Objectives:
- Become familiar with virtual machine configuration in different cloud platforms.
- Demonstrate the advantage of managed cloud services.
- Implement custom web applications in different cloud computing service models.
- Use advanced techniques to scale cloud resources under dynamic requirements.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Configure (C3) virtual machines (instances) with underlying storage mechanisms, supporting security and access mechanisms. |
|
CO2 |
Leverage (C3) managed database services for solving relational database needs. |
|
CO3 |
Implement (C3) web applications in IaaS and PaaS environments. |
|
CO4 |
Use (C3) load balancing and auto-scaling to automatically control virtual instances and distribute traffic across the instances. |
|
CO5 |
Design (C6) a custom cloud hosting solution for a given problem. |
|
CO6 |
Report (A3) lab activities and experimental results or findings. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
✓ |
✓ |
||||||||||
|
CO2 |
✓ |
✓ |
||||||||||
|
CO3 |
✓ |
✓ |
||||||||||
|
CO4 |
✓ |
✓ |
||||||||||
|
CO5 |
✓ |
✓ |
✓ |
✓ |
✓ |
|||||||
|
CO6 |
✓ |
Course Description:
|
SL No |
Course Content |
COs |
|
1. |
Introduction to AWS IAM |
CO1, CO5, CO6 |
|
2. |
Network and Content Delivery: Build VPC and Launch a Web Server |
CO1, CO5, CO6 |
|
3. |
Introduction to Amazon EC2, AWS Lambda, AWS Elastic Beanstalk |
CO2, CO3, CO5 |
|
4. |
Working with EBS |
CO1, CO5, CO6 |
|
5. |
Build a DB Server and Interact with the DB Using an App |
CO2, CO5, CO6 |
|
6. |
Scale and Load Balance Cloud Architecture |
CO4, CO5, CO6 |
Text Books, Reference Books and Other Resources:
- AWS Cloud Fundamentals Online Course Material
- Cloud Computing: A Hands-On Approach, by Arshdeep Bahga and Vijay Madisetti.
- Cloud Computing Theory and Practice, by Dan Marinescu, 2nd Edition.
- Cloud Computing: Principles and Paradigms, by Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, 1st Edition, Wiley
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO5 |
C3 |
Demonstration, discussion, experiment |
Performance, Lab, Quiz |
|
CO2 |
PO1, PO5 |
C3 |
Demonstration, discussion, experiment |
Performance, Lab, Quiz |
|
CO3 |
PO1, PO5 |
C3 |
Demonstration, discussion, experiment |
Performance, Lab, Quiz |
|
CO4 |
PO1, PO5 |
C3 |
Demonstration, discussion, experiment |
Performance, Lab, Quiz |
|
CO5 |
PO1, PO2, PO3, PO4, PO5 |
C6 |
Demonstration, discussion, experiment |
Performance, Lab, Quiz |
|
CO6 |
PO10 |
A3 |
Demonstration |
Report |
Course Title: Basic Accounting
Course Code: ACC 101
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Non-engineering | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course helps students to get basic knowledge of accounts and other business studies.
Course Objectives:
The objectives of this course are:
- To enable the students to study, understand and use the accounting process and accounting information.
- To introduce the students to accounting as a valuable tool of business, record keeping, generation of accounting information, analysis and interpretation and communication of the same to different interest groups and thereby achieving the predetermined goals of the organization.
- To teach the causes of non-equal balance of bank account of a company account and bank statement and also understand the bank transaction and function of bank.
- To measure cost per unit and total cost of a product.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) various concepts related to accounting system. |
|
CO2 |
Calculate (C3) the recording process of accounting system. |
|
CO3 |
Demonstrate (C3) the process of preparing financial statement for a problem. |
|
CO4 |
Illustrate (C3) various concepts and process of depreciation. |
|
CO5 |
Solve (C3) various problems of cost accounting and standard coding. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
√ |
||||||||||
|
CO2 |
√ |
√ |
||||||||||
|
CO3 |
√ |
√ |
||||||||||
|
CO4 |
√ |
√ |
||||||||||
|
CO5 |
√ |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Definition of Accounting and Financial Accounting, Users of Accounting Information, Branches of Accounting, Types of accounts, Determination of debit and credit, Accounting concepts and Conventions, Definition of business transaction, Nature of business transaction, Accounting Principles, GAAP, Accounting Cycle. |
CO1 |
|
2. |
Recording Process: Journal, Ledger, Trial Balance, Cash Book, adjusting entries, closing entries, classifying capital and revenue expenditure |
CO2 |
|
3. |
Preparation of Financial Statement: Definition, Features of financial statement, Component/parts of financial statement, Multi-step Income Statement, Owners Equity Statement, Classified Balance Sheet, Cash Flow Statement, Bank Reconciliation Statement. |
CO3 |
|
4. |
Depreciation: Definition of Depreciation, Objectives and methods for providing depreciation. |
CO4 |
|
5. |
Cost Accounting: Introduction, Objectives and advantages of cost accounting, Elements of cost, Preparation of cost sheet, Inventory valuation (Store ledger), Overhead allocation. |
CO5 |
|
6. |
Standard Costing: Calculation of material, labor and overhead variance, Break-even point, Margin of safety, Use of accounting information in project evaluation, Budget (cash budget and master budget). |
CO5 |
Text Books, Reference Books and Other Resources:
- Accounting Principles. by Weygandt, Kieso and Kimmel- Latest edition
- Cost Accounting by Bhabatosh Banarjee
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1, PO2 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1, PO2 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1, PO2 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO4 |
PO1, PO2 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO5 |
PO1, PO2 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
Course Title: Basic Economics
Course Code: ECO 201
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Non-engineering | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is a foundation course that will prepare students to understand fundamental microeconomic and macroeconomic concepts. The goal of this course is to provide some indispensable lessons about individual decision making, the role of the market as well as government in an economy.
Course Objectives:
The main objectives of this course are:
- Edify the concept of fundamental demand and supply mechanism in relation to individual decision making.
- Figure out the measurement of individual satisfaction and find out basic economic problems of society as well as make clear the basic ideas on firm and production.
- Understand and verify the objectives, goals, tools, and problems of macroeconomic concepts and public policies.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Explain (C2) Demand and supply concept as an apparatus of individual decision making and express individual satisfaction level numerically, graphically. |
|
CO2 |
Describe (C2) the acquired concepts to understand the nature of firm and production. |
|
CO3 |
Summarize (C2) the advantages and disadvantages of different macroeconomic situations and identify required policies. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
The Economic Problem, The Language of economics, Economic System, How the Economy works, Demand and Supply Theory, Elasticity, Consumer behavior and market demand, Production and Costs Theory, The perfectly competitive market and its characteristics, Imperfectly competitive markets, Basic principles of factor pricing, Resource allocation and the market, International trade, Non – Renewable resources, Key macroeconomics phenomena, Income determination, Balance of payments and the exchange rates |
CO1, CO2, CO3 |
Text Books, Reference Books and Other Resources:
- Gregory Mankiw: Principles of Economics; 6th edition
- J. Baumol and A.S. Blinder: Economics: Principles and Policies
- Robin Bade and Michael Parkin: Foundations of Microeconomics, 8th Edition
- Fisher, R. Dornbusch and Schmalensee: Economics, McGraw Hill Company, New York
- Modern Microeconomics: Theory and Application. H.L. Ahuja and S. Chand. Revised Edition.
CO Delivery and Assessment:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
Course Title: Industrial & Business Management
Course Code: MGT 203
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Non-engineering | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course is designed to familiarize students with the current management practices and the business environment in the modern world.
Course Objectives:
The main objectives of this course are:
- Introduce students to the industrial management concepts and functional areas of business.
- Acquaint students with the management skills needed for different organizational activities.
- Provide the knowledge of organizational structure & design
- Impart knowledge on basic Marketing & HRM concepts and functions
- Provide an understanding of financial and operational management tools and techniques.
- Apply the knowledge of organizational innovations to gain competitive advantages
- Facilitate students with necessary knowledge regarding leadership and ethical issues in organizations.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Demonstrate (C3) an understanding of industrial management concepts and practices. |
|
CO2 |
Identify (C1) the basic managerial role, skills, functions & the nature of managerial work for upcoming challenges in an organization. |
|
CO3 |
Analyze (C4) the implication of numerous elements of organizational structure & design. |
|
CO4 |
Explain (C2) the basic principles and functions of marketing & HRM. |
|
CO5 |
Understand (C2) and apply (C3) a variety of technical and analytical tools used by the financial and operations managers for decision making. |
|
CO6 |
Understand (C2) how to integrate organizational innovations to gain competitive advantages. |
|
CO7 |
Apply (C3) appropriate leadership practices and ethics in complex business environment. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
|||||||||||
|
CO4 |
√ |
|||||||||||
|
CO5 |
√ |
|||||||||||
|
CO6 |
√ |
|||||||||||
|
CO7 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Basic concepts-Industry, Business, management, industrial management, Types of Industry, why study industrial business management, objectives, Importance, Applications, Problems of industrial management. |
CO1 |
|
2. |
Management: Nature of management, levels of management, managerial roles, managerial skills, organizational hierarchy, managerial functions, the science and art of management, productivity, effectiveness and efficiency. Management theories-Classical & behavioral management, Principles of management, challenges of a manager. |
CO1 |
|
3. |
Organization: Meaning, organizational structure, departmentalization, work specialization, chain of command, span of control, centralization vs decentralization, formalization, common organizational design, simple structure, bureaucracy, matrix structure, team structure, virtual organization, boundary less organization. learning organization. |
CO2 |
|
4. |
Marketing: Definition, basic concepts (needs, wants and demands), marketing strategy: segmentation; targeting; positioning, marketing mix, holistic marketing, green marketing. |
CO4 |
|
5. |
Financial Management: Functions & scope, key activities of financial managers, principles of financial management, financial statements and reports, financial ratio analysis, types of financial ratios: liquidity ratios; asset management ratios; profitability ratios and market ratios, net present value (NPV), internal rate of return (IRR), break-even analysis, depreciation, time value of money, future value vs present value. |
CO5 |
|
6. |
Human Resource Management: Meaning, HRM planning, job analysis, recruitment, selection, selection process, selection techniques, employee training and development, performance appraisal, conflict management, health and safety measures. |
CO4 |
|
7. |
Operations Management: Definition, facility location, plant layout, inventory management, productivity, quality theories and characteristics, project planning (PERT, CPM). |
CO5 |
|
8. |
Innovation Management: Innovation and discovery, sources of innovative, types of innovation idea, role of creative thinking, creative climate, innovation process, principles of innovation, product life cycle, service innovation, intellectual property, patent, copyrights. |
CO6 |
|
9. |
Leadership & Ethics in Business: Definition and components, trait versus process leadership, assigned versus emergent leadership, leadership and power, leadership and management, transformational leadership, servant leadership, team leadership. Concept, domains of ethical theories, principles of personal & professional ethics, concepts of business ethics, importance of business ethics, values & ethics, characteristics of an ethical organization, legal vs ethical. |
CO7 |
Text Books, Reference Books and Other Resources:
- Griffin, R. W. (2005). Management (8th ed.). Houghton Mifflin Company.
- Robins, S. P., & Coulter, M. (2004). Management (8th ed.). Prentice Hall.
- Lee, J. K., Larry, P. R., & Manoj, K. M. (2006). Operations Managemen: Processes & Value Chains (8th ed.). New Jersey, USA: Prentice Hall.
- Kotler, P., Armstrong, G., Agnihotri, P. Y., & Haque, E. (2010). Principles of Marketing: A South Asian Perspective (13th ed.). Delhi: Pearson Prentice Hall.
- Brigham, E. F., & Houston, J. F. (2009). Fundamentals of Financial Management (10th/Latest ed.). Cengage Learning.
CO Delivery and Assessment:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO2 |
PO1 |
C1 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO3 |
PO1 |
C4 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO4 |
PO1 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO5 |
PO1 |
C2, C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO6 |
PO1 |
C2 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
|
CO7 |
PO1 |
C3 |
Lecture, PPT slides, problem solving |
Class Test, Assignment, Midterm, Final Exam |
Course Title: Organizational Behavior
Course Code: MGT 251
| Credits: 3 | Class Hours/Week: 3 |
| Course Type: Non-engineering | Pre-requisite: |
| CIE Marks: 60 | SEE Marks: 40 |
Course Rationale:
This course helps students to identify the human behavior in organizational settings. It studies individual and group behavior, organizational communication and structure, conflicts, and stress have on behavior within organization and the proper use of such knowledge improve an organization’s effectiveness.
Course Objectives:
The main objectives of this course are:
- Identify the complex nature of human beings in organizations through causes and effects of that behavior.
- Provide the knowledge of organizational communication, structure and culture.
- Discuss conflict resolution and change management in order to indoctrinate students how to handle a new workforce and cope with the challenges of new environment.
- Acquaint students with numerous approaches of stress management.
Course Outcomes (COs):
Upon successful completion of this course, students will be able to:
|
CO1 |
Describe (C2) numerous concepts, factors, challenges related to human behavior in organization. |
|
CO2 |
Explain (C2) the individual and team behavior in the organization. |
|
CO3 |
Discuss (C2) the structure and process of organization. |
Mapping of Course Outcomes to Program Outcomes:
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
|
CO1 |
√ |
|||||||||||
|
CO2 |
√ |
|||||||||||
|
CO3 |
√ |
Course Description:
|
SL No. |
Course Content |
COs |
|
1. |
Introduction: Meaning of OB, importance, goals of OB, developing an OB model, challenges and opportunities, organizational culture and its impacts, socialization practice, globalization, cultural dimension, cross-cultural management |
CO1 |
|
2. |
Behavior within Organization (The Individual): Workplace diversity, workplace discrimination, biographical characteristics, characteristics factor, intellectual and physical abilities, attitudes, job satisfaction, emotions and mood, affective events theory, emotional intelligence, personality, Myers-Briggs Type Indicator (MBTI) personality framework and the Big Five mode, core self-evaluation (CSE), self-monitoring, proactive personality, Hofstede’s five value dimensions and the GLOBE framework, perception, attribution theory, decision making, three-stage model of creativity, Contrast Effect, Halo Effect, Stereotyping. motivation, different motivational theories, justice, job engagement, changing work environment |
CO2 |
|
3. |
Behavior within Organization (Group and Interpersonal Influence): Types of groups, group development model, groups vs team, group effectiveness, group decision making, team arrangement, communication, types of communication, interpersonal communication, barriers to effective communication, cross-cultural communication, leadership, different theories of leadership, roles of leaders, leadership vs power, types of power, abuse of power, politics and political behavior, conflict, types and loci of conflict, conflict process, bargaining, negotiation, organizational structure, elements and characteristics of organizational structure, structural models, downsizing and its effects, behavioral implications |
CO2 |
|
4. |
Organizational Structure and Process: Organizational culture and its effects, factors for organizational culture, types of culture, effect of national culture on organizational culture, recruitment and selection methods, types of training, methods for performance evaluation, leadership role of HR, Forces for change, individual and organizational resistance to change, overcoming resistance to change. Stress management: Definition, Sources and Consequences, Managing Stress: Individual Approach and Organizational Approach. |
CO3 |
Text Books, Reference Books and Other Resources:
- Organizational Behavior. 15th ed. New Delhi (2014): Pearson/Prentice Hall by Robbins, S. P., Judge, T.A & Vohra, N.
- Organizations: behavior, structure, processes. 12th ed. McGraw Hill (2006) by Gibson, J., Ivanchevich, J., Donnelly, J. &Konopaske R.
Mapping Course Outcomes with the Teaching-Learning and Assessment Strategy:
|
COs |
Corresponding POs |
Bloom’s Taxonomy Domain/Level (C: Cognitive, P: Psychomotor A: Affective) |
Delivery Methods and Activities |
Assessment Tools |
|
CO1 |
PO1 |
C2 |
Lecture, Notes, Case Studies |
Class Test, Assignment, Mid Term, Final Exam |
|
CO2 |
PO1 |
C2 |
Lecture, Notes, Case Studies |
Class Test, Assignment, Mid Term, Final Exam |
|
CO3 |
PO1 |
C2 |
Lecture, Notes, Case Studies |
Class Test, Assignment, Mid Term, Final Exam |
|
Marks Range |
Letter Grade |
Grade Point |
|
|
80% and above |
A+ |
A Plus |
4.00 |
|
75% to less than 80% |
A |
A Regular |
3.75 |
|
70% to less than 75% |
A- |
A Minus |
3.50 |
|
65% to less than 70% |
B+ |
B Plus |
3.25 |
|
60% to less than 65% |
B |
B Regular |
3.00 |
|
55% to less than 60% |
B- |
B Minus |
2.75 |
|
50% to less than 55% |
C+ |
C Plus |
2.50 |
|
45% to less than 50% |
C |
C Regular |
2.25 |
|
40% to less than 45% |
D |
D Regular |
2.00 |
|
Less than 40% |
F |
0.00 |
|
Grade Point Average (GPA) and Cumulative Grade Point Average (CGPA):
Grade Point Average (GPA) is the weighted average of the grade points obtained in all the courses attempted by a student. The four-step procedure that will be followed to calculate the CGPA (Cumulative Grade Point Average) of a student is given below:
- Grade points earned in each course will be computed by multiplying the credit (Ci) and the individual grade point (Gi) earned in that course (i.e., Ci*Gi).
- The grade points (determined in step i) of all the attempted courses will be added to determine the total grade point earned (i.e., ∑Ci*Gi).
- Credits of all courses will be added together to determine the total credits (∑Ci).
- CGPA will be determined by dividing the result of step (ii) by the result of step (iii). For example, if a student attempted n courses in a semester having credits C1, C2, … , Cn and his/her grade points in these courses are G1, G2, … , Gn respectively, then the CGPA can be calculated as follows:
CGPA = 
A Numerical Example
Suppose a student has completed six courses in a semester and obtained the following grades:
|
Course |
Credit Ci |
Letter Grade |
Grade Point Gi |
Ci * Gi |
|
MAT 111 |
3.0 |
A+ |
4.00 |
12.00 |
|
ECO 101 |
3.0 |
A |
3.75 |
11.25 |
|
CSE 101 |
3.0 |
A+ |
4.00 |
12.00 |
|
STA 101 |
3.0 |
F |
0.00 |
0.00 |
|
ENG 101 |
3.0 |
A |
3.75 |
11.25 |
|
MAT 121 |
1.5 |
B |
3.00 |
4.50 |
|
Total |
∑Ci= 16.5 |
∑ Ci * Gi = 51.00 |
CGPA = (51.00 / 16.50) = 3.09
Note: If the 3rd digit after decimal points is above ‘0’, grade will be rounded (ceiling) into the second digit after decimal. For example, 2.990 will be counted as 2.99 while 2.991 will be counted as 3.00 in CGPA calculation.
Delivery Methods and Activities
- Lecture
- Digital Learning
- Video or Animation
- Interactive Lecture
- Mathematical Problem solving
- Group Discussion
- Student Presentation
Student Assessment Tools:
- Class Assessment - 10%
- Assignment/ Class Performance - 10%
- Class test- 20%
- Mid Term-20%
- Final Exam -40%
Delivery Methods and Activities
- Interactive Lecture
- Experiment done by Students
- Student Presentation
- Student Demonstration
Student Assessment Tools:
- Class Assessment - 10%
- Lab Performance - 40%
- Report- 20%
- Quiz/Written Exam-20%
- Viva -10%
Delivery Methods and Activities
- Interactive Lecture
- Experiment done by Students
- Student Presentation
- Student Demonstration
- Project
Student Assessment Tools:
- Class Assessment - 10%
- Lab Performance - 40%
- Project- 30%
- Presentation/Viva-20%
- Report -20%
Delivery Methods and Activities
- Interactive Lecture
- Student Demonstration
- Discussion
- Experiment done by Students
Student Assessment Tools:
- Class Assessment - 10%
- Lab Performance - 20%
- Report- 10%
- Lab Exam-30%
- Quiz/Written Exam-20%
- Viva -10%
Delivery Methods and Activities:
- Lecture
- Video Presentation
- Interactive Discussion
- Pair work
- Audiotapes
- Presentation
- Selected Stories
Student Assessment Tools:
- Class Assessment -10%
- Class participation/ Group work -30%
- Quiz/Class Test/Assignment- 30%
- Presentation- 20%
- Viva - 10%
Teaching-Learning Strategy
- Instructions
- Reading Materials/PPT slides
- Tutorials, E-Learning
- Student Presentation
- Group Work: Assignments, Discussions, Investigations, Presentations
- Case Studies
Assessment Strategy
- Project Report – 30%
- Presentation – 30%
- Project Demo – 40%
Quick Links and Contacts
- Application - Admission (Demo Copy)
- Application - Student ID
- Application - Migration
- Application - Free Studentship
- Application - Hostel Seat
- Application - Enrollment (Demo Copy)
- Verification Procedure
- Application for Certificate & Procedure
- Money Receipt (Demo Copy)
- Student's Code of Conduct
Student's Link
-
541, O.R.Nizam Road, GEC Circle, Chittagong.
-
1/A,O.R.Nizam Road,Prabartak Circle, Panchlaish, Chittagong.
-
Phone: +8809610828282.
-
Admission Office: +8801313044515-17
-
Accounts Office:
-
Controller of Examinations: +8801313044518
Email : controller@puc.ac.bd -
IT Office: +8801313044519 (Bkash)
-
info@puc.ac.bd