CSE-AIML

6th Semester

• MS-302 Principles of Management for Engineers [3]
• HS-304 Universal Human Values [1]
• DA-304T Statistics, Statistical Modelling & Data Analytics [3]
• AI-302T Artificial Intelligence [3]
• AI-320T Optimization Techniques [3]
• ML-352T Supervised and Unsupervised Learning [3]
• SE-354T Software Project Management [3]
• DA-304P Statistics, Statistical Modelling & Data Analytics Lab [1]
• AI-302P Artificial Intelligence Lab [1]
• AI-320P Optimization Techniques Lab [1]
• ML-352P Supervised and Unsupervised Learning Lab [1]
• SE-354P Software Project Management Lab [1]
• HS-352 NSS/ NCC/ Cultural Clubs/ Technical Society/ Technical Club [2]

5th Semester

• HS-301 Economics for Engineers [2]
• CIC-303 Compiler Design [3]
• CIC-305 Operating Systems [4]
• CIC-307 Computer Networks [4]
• CIC-309 Software Engineering [3]
• CIC-311 Design and Analysis of Algorithm [4]
• CIC-351 Compiler Design Lab [1]
• CIC-353 Operating Systems Lab [1]
• CIC-355 Computer Networks Lab [1]
• CIC-357 Software Engineering Lab [1]
• CIC-359 Design and Analysis of Algorithm Lab [1]
• [NUES]Internship ES-361 Summer Training Report - [1]

4th Semester

• BS-202 Probability, Statistics and Linear Programming [4]
• HS-204 Technical Writing [2]
• CIC-206 Theory of Computation [4]
• EEC-208 Circuits and Systems [4]
• CIC-210 Database Management Systems [4]
• CIC-212 Programming in Java [4]
• BS-252 Probability, Statistics and Linear Programming Lab [1]
• EEC-254 Circuits and Systems Lab [1]
• CIC-256 Database Management Systems Lab [1]
• CIC-258 Programming in Java Lab [1]

3rd Semester

• ES-201 Computational Methods [4]
• HS-203 Indian Knowledge System [2]
• CIC-205 Discrete Mathematics [4]
• ECC-207 Digital Logic and Computer Design [4]
• CIC-209 Data Structures [4]
• CIC-211 Object-Oriented Programming using C++ [4]
• ES-251 Computational Methods Lab [1]
• ECC-253 Digital Logic and Computer Design Lab [1]
• CIC-255 Data Structures Lab [1]
• CIC-257 Object-Oriented Programming using C++ Lab [1]

2nd Semester

• ES-102 Programming in ‘C’  [3]  or  BS-104 Applied Chemistry [3]
• BS-106 Applied Physics-II [3]       
• ES-108 Electrical Science [3]      or   BS-110 Environmental Studies [3]
• BS-112 Applied Mathematics - II [4]
• HS-114 Communications Skills [3]  or  HS-118 Human Values and Ethics [1]
• ES-114 Engineering Mechanics [3]
• BS-152 Physics-II Lab [1]
• ES-154 Programming in ‘C’ Lab [1]   or   BS-156 Applied Chemistry Lab [1]
• ES-158 Engineering Graphics-II [1]
• ES-160 Electrical Science Lab [1]     or    BS-162 Environmental Studies Lab [1]
• ES-164 Workshop Practice [2]

1st Semester

• ES-101 Programming in ‘C’  [3]  or  BS-103 Applied Chemistry [3]
• BS-105 Applied Physics-I [3]       
• ES-107 Electrical Science [3]      or   BS-109 Environmental Studies [3]
• BS-111 Applied Mathematics - I [4]
• HS-113 Communications Skills [3]  or  HS-117 Human Values and Ethics [1]
• ES-119 Manufacturing Process [4]
• BS-151 Physics-I Lab [1]
• ES-153 Programming in ‘C’ Lab [1]   or   BS-155 Applied Chemistry Lab [1]
• ES-157 Engineering Graphics-I [1]
• ES-159 Electrical Science Lab [1]     or    BS-161 Environmental Studies Lab [1]

Program Specific Outcomes (PSOs) for AI & ML Department

1. AI & ML Solution Development – Graduates will be able to design, develop, and deploy AI and ML-based solutions by leveraging modern tools, algorithms, and frameworks to solve real-world problems across various domains.
2. Ethical & Impactful AI Implementation – Graduates will demonstrate the ability to apply AI and ML technologies responsibly, considering ethical, societal, and environmental impacts while ensuring fairness, transparency, and security in AI-driven systems.

Program Educational Objectives (PEOs) for AI & ML Department

1. Strong Technical Foundation & Lifelong Learning – Graduates will develop a strong foundation in Artificial Intelligence and Machine Learning principles, enabling them to adapt to evolving technologies through continuous learning and advanced studies.
2. Innovative Problem-Solving & Research – Graduates will be equipped with analytical and problem-solving skills to conduct research, innovate, and develop AI-driven solutions addressing industry and societal challenges.
3. Professional Ethics & Leadership – Graduates will demonstrate ethical responsibility, teamwork, and leadership qualities in their professional careers, ensuring the responsible development and deployment of AI technologies for the betterment of society.

PROGRAM OUTCOMES (POs)

1. Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.
2. Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
3. Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)
4. Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions.
5. Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems.
6. The Engineer & The World: Analyze and evaluate societal & environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development
8. Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws.
9. Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
10. Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences.
11. Project Management & Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.
12. Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change.