AI & Machine LearningSemester 4-1 syllabus

The first semester of final year centers on Reinforcement Learning as the last major AI/ML core course, paired with Human Resource & Project Management to build workplace-readiness skills. Two Professional Elective slots open onto emerging-technology tracks — from Responsible AI and Blockchain to High Performance Computing and Big Data Analytics — while two Open Electives broaden exposure further. A Prompt Engineering skill course reflects the rise of generative AI tooling, and an evaluated industry internship/mini-project closes out the pre-capstone coursework.

Subjects

Reinforcement Learning

• Unit 1: The reinforcement learning problem and its core elements.
• Unit 2: Multi-armed bandits and action-value methods.
• Unit 3: Finite Markov decision processes and the agent-environment interface.
• Unit 4: Monte Carlo methods for prediction and control.
• Unit 5: Applications and case studies, including TD-Gammon and the Acrobot problem.

L-T-P: 3-0-0, 3 credits

Human Resource & Project Management

(Management Course-II)

• Unit 1: HRM nature, scope, and the functions of an HR manager.
• Unit 2: Human resource development, training models, and HR accounting.
• Unit 3: Project management basics, including resource management and project environment.
• Unit 4: Project types and the unique management challenges each presents.
• Unit 5: Project implementation and review, including organizational forms and planning.

L-T-P: 2-0-0, 2 credits

Professional Elective-IV options:

• Responsible AI — covers an overview of AI and its common risks, fairness and bias types, explainability and interpretability techniques, safety/security/privacy concerns, and real-world case studies of AI failures.
• Blockchain Technology — covers blockchain fundamentals and its borrowed technologies, consensus mechanisms like Proof of Work, Ethereum and the Ethereum Virtual Machine, and enterprise blockchain via Hyperledger Fabric.
• Quantum Computing — covers the historical and mathematical foundations of quantum computing, qubits and their physical implementations, quantum algorithms, and noise/error correction.
• Robotic Process Automation — covers RPA scope and techniques, record-and-play automation with UiPath, data manipulation and control logic, exception handling in assistant bots, and bot deployment/maintenance.

L-T-P: 3-0-0, 3 credits (one option selected)

Professional Elective-V options:

• Agile Methodologies — covers agile management theory, agile processes like Scrum and Feature-Driven Development, agile knowledge sharing via story cards, agility’s impact on requirements engineering, and agile quality assurance.
• Augmented Reality & Virtual Reality — covers AR fundamentals and computer-vision-based tracking, VR fundamentals and history, the physiology of human vision, and motion perception in real and virtual environments.
• High Performance Computing — covers the motivation and scope of parallelism, parallel algorithm design principles, basic communication operations, analytical performance models, and parallel sorting/graph algorithms.
• Big Data Analytics — covers Java data structures for big data work, foundational big-data infrastructure (GFS, HDFS), MapReduce programming, stream processing with Spark, and Pig for simplified Hadoop programming.

L-T-P: 3-0-0, 3 credits (one option selected)

Open Elective-III and Open Elective-IV are drawn from the cross-department elective pool, following the same structure as earlier open electives.

Prompt Engineering

(Skill Enhancement Course; alternative: SWAYAM Plus certificate in Prompt Engineering and ChatGPT)

• Unit 1: Foundations of prompt engineering and how it differs from traditional programming.
• Unit 2: Advanced prompt patterns and techniques, including enhanced prompt anatomy and contextual detail.
• Unit 3: Structured outputs and reasoning techniques for reliable LLM responses.
• Unit 4: Retrieval-augmented generation and LangChain-based workflows.
• Unit 5: LLM agents, multimodal AI, and ethical evaluation of generative systems.

L-T-P: 0-1-2, 2 credits

Constitution of India

(Audit Course)

• Unit 1: The history and drafting of the Indian Constitution.
• Unit 2: Fundamental rights and duties, including the right to equality.
• Unit 3: The organs of governance, including Parliament’s composition and functions.
• Unit 4: Local administration and district-level governance.
• Unit 5: The Election Commission’s role and functioning.

L-T-P: 2-0-0 (non-credit audit course)

The Industry Internship/Mini-Project undertaken over the summer is evaluated this semester for 2 credits.

Students may optionally pursue Honors-pool electives such as Agentic AI (covering agentic intelligence foundations, decision-making and planning, LLM-driven agent behaviour, agent frameworks and system design, and responsible applied agentic AI) or Adversarial Machine Learning (covering ML/deep-learning foundations, adversarial attack techniques, defense mechanisms and robust training, privacy/backdoor threats, and advanced topics including GAN-based attacks), alongside a Minor-pool course from the same specialization track chosen in earlier semesters.

Semester total: 19-1-2 contact hours, 21 credits.