The curriculum of the program offers 144 credits of Required courses and 16 credits of Elective courses including basic science, language, mathematics, core, and nonengineering 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 
NonEngineering 
12 Credits 
Program Educational Objectives (PEO): Within 35 years of graduation, the graduates of CSE will be able to:
PEO1: Think Critically: Use problemsolving, decisionmaking and research skills to identify and solve complex problems needed to pursue a diverse range of professions.
PEO2: Implementation Efficiency: Develop and implement efficient, sustainable, scalable, manageable, and futureproof solutions to problems through continuous learning.
PEO3: Society, Ethics and Team Player: ethically manage independent or team work considering the societal, health and safety, and environmental impact.
PEO4: Communication: Graduates will be able to disseminate information clearly and precisely to a broad range of audiences.
Missions 
PEO1 
PEO2 
PEO3 
PEO4 
Mission 1: 
√ 
√ 


Mission 2: 
√ 
√ 


Mission 3: 
√ 
√ 
√ 

Mission 4: 


√ 
√ 
Mission 5: 
√ 
√ 
√ 
√ 
Mission 6: 
√ 
√ 
√ 
√ 
Mission 7: 
√ 
√ 
√ 
√ 
The BSCSE 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 BScCSE 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 researchbased 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 multidisciplinary 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 decisionmaking and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO12: Lifelong learning: Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.
PO No. 
PO Statement 
PEO1 
PEO2 
PEO3 
PEO4 
Thinking Critically 
Implement Efficiently 
Society, Ethics, and Team Player 
Communication 

PO1 
Engineering Knowledge 
√ 

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 
Lifelong 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, theorybased understanding of the natural sciences applicable to the discipline
K2: Conceptuallybased mathematics, numerical analysis, statistics and formal aspects of computer and information science to support analysis and modelling applicable to the discipline
K3: A systematic, theorybased 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 problemsolving ranges or features.
P1 (Depth of knowledge required) Cannot be resolved without indepth engineering knowledge at the level of one or more of K3, K4, K5, K6 or K8 which allows a fundamentalsbased, first principles analytical approach.
P2 (Range of conflicting requirements) Involve wideranging 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 subproblems.
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 wideranging or conflicting technical, engineering or other issues.
A3 (Innovation) Involve creative use of engineering principles and researchbased 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 principlesbased 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 
NonEngineering (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
Termwise 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 
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  
K1K4  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  Lifelong Learning  Science  Math  Engg. Fundamentals  Engg. Specialization  Design  Technology  Society  Research  Knowledge k3k6,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  Prerequisite: 
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:
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 displacementtime, velocitytime and accelerationtime. 
CO1 
2. 
Motion in two and three dimensionsprojectile motion, Application of Newton’s laws of motion; Equilibrium forces. Workkinetic energy theorem. Power; Conservation of energy, Conservation of linear momentum for a system of particles. Centerofmass 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:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 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:
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 biprism, 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, MichelsonMorley experiment, LorenzEinstein transformation, Mass energy relation, Quantum effect, Photoelectric effect, Compton Effect; 
CO1, CO2, CO3 
10. 
Atomic Physics: DeBroglie wave, correspondence principles, uncertainty principle, The RutherfordBohr 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, Halflife, 
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:
References:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 
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:
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 











C O2 











C O3 










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/yesno questions 
CO3 
Text Books : (for grammar purpose)
Author Book Name
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 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:
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 












C O2 












C O3 










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, email, 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:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 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 informationdriven 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:
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 








√ 
√ 


C O2 




√ 



√ 
√ 


C O3 








√ 
√ 


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 prosepassages 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:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 
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:
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 
√ 
√ 










CO2 
√ 
√ 










CO3 
√ 
√ 










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 coefficient 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 coordinate 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:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 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:
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 
√ 











CO2 
√ 











CO3 
√ 











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 
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 
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:
Ordinary and Partial Differential Equations: by M D. Raisinghania
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 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:
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) realworld problems using various probability models. 
Mapping of Course Outcomes to Program Outcomes:

PO1 
PO2 
PO3 
PO4 
PO5 
PO6 
PO7 
PO8 
PO9 
PO10 
PO11 
PO12 
C O1 
√ 











C O2 
√ 











C O3 
√ 











CO4 
√ 











Course Description:
SL No. 
Course Content 
COs 
1. 
Complex Number System, Analytic Function, Harmonic Function CauchyRiemann 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:
M apping Course Outcomes with the TeachingLearning 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  Prerequisite: 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:
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 viceversa. 
CO4 
Solve (C3) basic properties, inverse properties, differential and integral equations using Laplace Transformation. 
Mapping of Course Outcomes to Program Outcomes:

PO1 
PO2 
PO3 
PO4 
PO5 
PO6 
PO7 
PO8 
PO9 
PO10 
PO11 
PO12 
C O1 
√ 











C O2 
√ 











C O3 
√ 











CO4 
√ 











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 CayleyHamilton 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:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 
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:
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 

CO1 
√ 

CO2 
√ 

CO3 
√ 
√ 

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, dowhile), 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 DoWhile Statements with Examples.

CO3, CO4 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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  Prerequisite: 
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:
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 

CO1 
√ 
√ 

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, Seriesparallel 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, Seriesparallel AC circuits. Reasoning Circuit: Series and Parallel circuits. 
CO1, CO2 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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
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 

CO1 
√ 
√ 

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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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, multiview 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 

CO1 
√ 
√ 

CO2 
√ 
√ 

CO3 
√ 
√ 

CO4 
√ 
√ 
√ 

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 stateoftheart 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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 

CO1 
√ 

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:
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 Prerequisite: 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:
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 userdefined 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 (ifelse, nested ifelse, switchcase, goto) 
CO2 
3. 
Control Statement: Looping (for, while, dowhile, nested looping), break and continue statement 
CO2 
4. 
Onedimensional Array, Multidimensional array, String, Array of Strings, user defined function, recursion function, pointers, structure & union.

CO2, CO3 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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, filehandling, C program without using conditional and loop statements 
CO1, CO6 
2. 
Problem solving using Control Structures and loops (ifelse, nested ifelse, switchcase, for loop, nested for loops, while loops, dowhile loops), one dimensional array and multidimensional 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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 
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) electronicsrelated 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. 
PN junction as a circuit element: Intrinsic and extrinsic semiconductors, operational principle of pn junction, contact potential, currentvoltage 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. 
CO1CO4 
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 midband 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. 
Metaloxidesemiconductor fieldeffecttransistor (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; Singlestage MOS amplifiers, MOSFET as a switch, CMOS inverter.

CO1 CO4 
5. 
Junction fieldeffecttransistor (JFET): Structure and physical operation of JFET, transistor characteristics, pinchoff voltage. Differential and multistage amplifiers, Description of differential amplifiers, smallsignal operation, differential and common mode gains, RC coupled midband frequency amplifier. 
CO1CO4 
6. 
Active filters: Basics of OpAmp, its characteristics, Different types of OpAmp 
CO1, CO3, CO4 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 vi 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 Prerequisite: SP 
CIE Marks: 60 SEE Marks: 40 
Course Rationale:
To empower the learner to perceive the fundamental knowledge of objectoriented programming paradigm and aimed at developing the skills of analyzing and solving realworld problems.
Course Objectives:
The objectives of this course are to:
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 objectoriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. 
CO3 
Demonstrate (C3) objectoriented features: exception handling, multithreading, 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 objectoriented programming (OOP), benefits and application areas of ObjectOriented 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, userdefined 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 filerelated programs to check the I/O. Basic filerelated 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: SPL 
CIE Marks: 60 SEE Marks: 40 
Course Rationale:
To empower the learner to perceive the fundamental knowledge of objectoriented programming paradigm and aimed at developing the skills of analyzing and solving realworld problems.
Course Objectives:
The objectives of this course are to:
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 objectoriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. 
CO3 
Implement (C3) objectoriented features: exception handling, multithreading, 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 statementrelated 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, userdefined 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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), Breadthfirst Search, Depthfirst Search 
CO2, CO3, CO4 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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. 
Flipflops: SR, JK, Master slave, T and D type flipflops and their characteristic tables & equations; Triggering of flipflops, 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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 4Bit 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 4bit Synchronous counter. 
CO1, CO2, CO3 
10. 
Design and verify the 4bit Asynchronous counter. 
CO1, CO2, CO3 
11. 
Familiarization of different types of flipflops. 
CO1, CO2, CO3 
Text and Reference books:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 vi 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 Prerequisite: SP 
CIE Marks: 60 SEE Marks: 40 
Course Rationale:
To empower the learner to perceive the fundamental knowledge of objectoriented programming paradigm and aimed at developing the skills of analyzing and solving realworld problems.
Course Objectives:
The objectives of this course are to:
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 objectoriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. 
CO3 
Demonstrate (C3) objectoriented features: exception handling, multithreading, 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 objectoriented programming (OOP), benefits and application areas of ObjectOriented 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, userdefined 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 filerelated programs to check the I/O. Basic filerelated 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: SPL 
CIE Marks: 60 SEE Marks: 40 
Course Rationale:
To empower the learner to perceive the fundamental knowledge of objectoriented programming paradigm and aimed at developing the skills of analyzing and solving realworld problems.
Course Objectives:
The objectives of this course are to:
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 objectoriented principles (Encapsulation, Polymorphism, Abstraction and Inheritance) to solve engineering problems. 
CO3 
Implement (C3) objectoriented features: exception handling, multithreading, 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 statementrelated 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, userdefined 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
of writing efficient programs.
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
structures in the context of writing efficient programs.
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), Breadthfirst Search, Depthfirst Search 
CO2, CO3, CO4 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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. 
Flipflops: SR, JK, Master slave, T and D type flipflops and their characteristic tables & equations; Triggering of flipflops, 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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 4Bit 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 4bit Synchronous counter. 
CO1, CO2, CO3 
10. 
Design and verify the 4bit Asynchronous counter. 
CO1, CO2, CO3 
11. 
Familiarization of different types of flipflops. 
CO1, CO2, CO3 
Text and Reference books:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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:
Mapping of Course Outcomes with TeachingLearning 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 Prerequisite: 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:
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: BellmanFord, 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:
2 Fundamentals of Computer Algorithms, Sartaj Sahni and Sanguthevar Rajasekaran Ellis Horowitz
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 Prerequisite: 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:
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: ICS 
CIE Marks: 30 SEE Marks: 70 
Course Rationale:
This course is designed to introduce the concept of realworld database design through the implementation of a databasedriven realtime project.
Course Objectives:
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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, FV analogy, FI analogy, Mechanical coupling Device, Electromechanical Systems.

CO4 
4. 
Linear differential equationI: Overview of linear differential equationI, Solution of higher order linear differential equation with constant coefficient. 
CO1 
5. 
Linear differential equationII: Overview of linear differential equationII, Solution of higher order linear differential equation with undetermined coefficient. 
CO1 
6. 
Lumped element electrical systems: Lumped element electrical systems using linear differential equationI Lumped element electrical systems using linear differential equationII Lumped element electrical systems using linear differential equationIII 
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 distortionless 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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Type: Core Prerequisite: 
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
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. 
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:
PO1 
PO2 
PO3 
PO4 
PO5 
PO6 
PO7 
PO8 
PO9 
PO10 
PO11 
PO12 

CO1 
√ 
√ 

CO2 
√ 
√ 
√ 
Text and Reference books:
Course Description:
SL No 
Course Content 
CLOs 
1. 
Laboratory work based on theory course EEE 201: Signals and Systems 
CO1 – CO2 
Mapping Course Outcomes with the TeachingLearning 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 
Course Title: Computational Methods for Engineering Problems 
Course Code: CSE 301 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: EM III 
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:
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. 
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:
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. 
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:
Mapping Course Outcomes with the TeachingLearning 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 
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 
CO5 
PO1, PO2 
C3 
Lectures, Notes, Practice Problems 
Class Test, Assignment, Midterm, Final Exam 
Course Title: Computational Methods for Engineering Problems Laboratory 
Course Code: CSE 302 
Credits: 0.75 Class Hours/Week: 1.5 
Course Type: Core Prerequisite: EM I, EM II, EM III 
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:
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 

CO1 
√ 
√ 
√ 

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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Title: Software Engineering & Information System Design 
Course Code: CSE 305 
Credits: 4 Class Hours/Week: 4 
Course Type: Core Prerequisite: DMS 
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:
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 

CO1 
√ 











CO2 
√ 
√ 










CO3 

√ 
√ 









CO4 
√ 











CO5 
√ 











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, CauseEffect, 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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Code: CSE 306 
Credits: 1.5 Class Hours/Week: 3 
Course Type: Core Prerequisite: 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:
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 clientside and serverside 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 

CO1 

√ 

CO2 
√ 
√ 
√ 
√ 

CO3 
√ 
√ 
√ 
√ 
√ 
Course Description:
SL No. 
Course Content 
COs 
1. 
Project Management: Project collaboration, Task Management 
CO1 
2. 
Implementation: Client side and serverside 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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Code: EEE 309 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: 
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:
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 & Demultiplexing. 
CO5 
Design (C6) Communication system 
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 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, Marray digital modulation, QAM, QPSK, Delta modulation, Multi carrier modulation, line coding, Frame construction, Error Probability. Introduction to Radar and Satellite Communication. ISDN, BISDN, SONET, SDH modulations, ASK, FSK, PSK, DPSK, MSK, Marray digital modulation, QAM, QPSK, Delta modulation, Multi carrier modulation, line coding, Frame construction, Error Probability. Introduction to Radar and Satellite Communication. ISDN, BISDN, 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:
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 
Course Code: CSE 310 
Credits: 1.5 Class Hours/Week: 3 
Course Type: Core Prerequisite: 
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
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:
Mapping Course Outcomes with the TeachingLearning 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 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: 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:
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 realworld 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 

CO1 
√ 

CO2 
√ 

CO3 
√ 

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 Coprocessor; 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, DMAbased 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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) microcontroller 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 reallife problems. 
CO2 
Investigate (C4) statistical methods and machine learning techniques for solving complex AIrelated problems 
CO3 
Use (C3) Natural Language Processing methods for reallife 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 ngrams), 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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 realworld applications.
Course Objectives:
The objective of the course is to enable the students to
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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 memorymanagement 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, Computersystem organization, and architecture, Operations, Computing environments. 
CO1 
2. 
OperatingSystem 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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, FloatingPoint 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
Course Outcomes (COs):
Upon successful completion of this course, students will be able to
CO1 
· Implement (C3) various serverside and clientside concepts using latest framework. 
CO2 
Use (C3) 3^{rd} 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, Clientside technologies, Serverside technologies, Report Writing with LATEX, Project Requirements 
CO1, CO2, CO3 
2. 
Serverside and Clientside concepts: Design pattern, Routing, Interaction with database, CRUD operation, Authentication and Authorization, Validation, File Uploading, ClientServer Communication, API integration, Responsive Designs, 3^{rd} 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 
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:
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: DigitaltoAnalog Conversion, Constellation Diagram 
CO3 
4. 
Modulation and demodulation: amplitude modulation, frequency and phase Modulation Analog Transmission: Digitalto 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 subnetworks, 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: Transportlayer services, 3.2 multiplexing and demultiplexing, connectionless transport: UDP function, The TCP Connection, TCP Segment Structure, RoundTrip 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, intraAS 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? ErrorDetection and Correction Techniques: Parity Checks, Multiple Access Links and Protocols: Channel Partitioning Protocols, Random Access Protocols, TakingTurns Protocols, Switched Local Area Networks: LinkLayer Addressing and ARP, MAC Addresses, Address Resolution Protocol (ARP), Sending a Datagram off the Subnet, Ethernet, Ethernet Frame Structure, Ethernet Technologies, LinkLayer Switches: Forwarding and Filtering, SelfLearning, Properties of LinkLayer 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:
Instructor contents and PPT slides: http://gaia.cs.umass.edu/kurose_ross/instructor.php
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: ICS 
CIE Marks: 70 SEE Marks: 30 
Course Rationale:
This subject aims to teach an understanding of computer networks and systems design through handson lab works and analysis with real world applications.
Course Objectives:
The objective of the course is to enable the students to
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 linkstate 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 handson. 
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:
 Instructor contents and PPT slides: http://gaia.cs.umass.edu/kurose_ross/instructor.php
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 
Contextfree 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:
Mapping CO with the TeachingLearning 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 Prerequisite: 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:
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, PacketFilter 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 Singlelayer (Perceptron) and Multilayer 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 (nonlinearity), 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. 
MultiLayer NN: Concepts of Hidden Layer, XOR Calculation Using Summation Formula, ReLU Activation Function, Vectorized Representation of MultiLayer 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, Backpropagation 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. Nonconvex, Local Vs. Global Optima, Log/CrossEntropy 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: Backprop 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, Alfacuts. 
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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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 realworld applications.
Course Objectives:
The objectives of the course are:
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 Multilayer 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, Settingup 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 MultiLayer 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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Code: CSE 455 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: SP 
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:
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:
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. 
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, antialiasing 
CO2 
3. 
2D and 3D Transformation, viewing, clipping: Geometric transformation, translation, rotation, scaling, mirror reflection, coordinate 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, Bitplane coding, Wavelet coding, watermarking, thresholding, segmentation, feature extraction. 
CO5 
Text Books, Reference Books and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 
Course Title: Computer Graphics & Image Processing Laboratory 
Course Code: CSE 456 
Credits: 1 Class Hours/Week: 2 
Course Type: Core Prerequisite: SPL 
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
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:

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. 
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:
Mapping Course Outcomes with the TeachingLearning 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 
Course Title: Control Systems 
Course Code: EEE 313 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: SS 
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:
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:
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: 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: Openloop stability, Poles Zeros state, space representation/transfer function/zeropole 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, Closedloop sensitivity functions, LQR design, pole placement, lead compensation, lag compensation, leadlag 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. 
Nonlinear control: Introduction to nonlinear control, Lyapunov stability criteria. Introduction to neural and fuzzy control. 
CO6 
Textbooks, References and Other Resources:
Mapping Course Outcomes with the TeachingLearning 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 
Course Code: EEE 314 
Credits: 1.5 Class Hours/Week: 3 
Course Type: Core Prerequisite: SSL 
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:
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 

CO1 
√ 
√ 
√ 

CO2 
√ 
√ 

CO3 
√ 
Course Description:
SL No. 
Course Content 
COs 
1. 
Laboratory work based on theory course EEE 313. It will cover hardwarebased 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:
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 
Course Code: CSE 400 
Credits: 4 Class Hours/Week: 4 
Course Type: Core Prerequisite: 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:
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 multidisciplinary and multicultural 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 

CO1 
√ 
√ 
√ 
√ 

CO2 
√ 
√ 

CO3 
√ 
√ 

CO4 
√ 
√ 
√ 

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 realworld computing problem. The types of research projects may include researchintensive, 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:
Mapping Course Outcomes with the TeachingLearning 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 inperson 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 inperson or virtual, Web links, Reference material 
Performance, Report, and Presentation 
Course Title: Compiler Construction 
Course Code: CSE 453 
Credits: 3 Class Hours/Week: 3 
Course Type: Core Prerequisite: 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:
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) contextfree 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 computerbased 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 tradeoff 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 
√ 
√ 

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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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 scikitlearn, 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 crossvalidation 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, KMeans 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: AI 
CIE Marks: 60 SEE Marks: 40 
Course Rationale:
This course will study stateoftheart 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:
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 realworld 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, VCDimensions 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: Distancebased 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: kmeans 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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
Course Outcomes:
Upon successful completion of this course, students will be able to
CO1 
Apply (C3) pattern recognition algorithms to realworld 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 opensource dataset using stateoftheart models 
CO3, CO4 
Text and Reference Books:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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:
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, Onpremises 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, Sitetosite VPN, VPC Transit Gateway, Connecting onpremises 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: WellArchitected 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:
Mapping Course Outcomes with the TeachingLearning 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 Prerequisite: 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 realworld cloud platforms.
Course Objectives:
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 autoscaling 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:
Mapping Course Outcomes with the TeachingLearning 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: Nonengineering  Prerequisite: 
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:
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, Multistep 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, Breakeven 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:
Mapping Course Outcomes with the TeachingLearning 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: Nonengineering  Prerequisite: 
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:
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:
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: Nonengineering  Prerequisite: 
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:
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 conceptsIndustry, 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 theoriesClassical & 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), breakeven 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:
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: Nonengineering  Prerequisite: 
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:
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, crosscultural 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, MyersBriggs Type Indicator (MBTI) personality framework and the Big Five mode, core selfevaluation (CSE), selfmonitoring, proactive personality, Hofstede’s five value dimensions and the GLOBE framework, perception, attribution theory, decision making, threestage 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, crosscultural 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:
Mapping Course Outcomes with the TeachingLearning 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 fourstep procedure that will be followed to calculate the CGPA (Cumulative Grade Point Average) of a student is given below:
CGPA =
A Numerical Example
Suppose a student has completed six courses in a semester and obtained the following grades:
Course 
Credit C_{i} 
Letter Grade 
Grade Point G_{i} 
C_{i} * G_{i} 
MAT 111 
3.0 
A+ 
4.00 
12.00 
ECO 101 
3.0 
A 
3.75 
11.25 
CSE 101 
3.0 