M.Tech Curriculum

M. Tech (CSE) Curriculum – Dept. of Computer Science & Engineering - July 2024 onwards

Approved in DCC Meeting Part A, held on Nov 2nd, 2023; Approved by Senate.

Semester 1

Sem	Course No	Course Title	Lecture	Tutorial	Ext. Tut.	Lab	Time outside class	Credits
1	DPE1, DPE2	ONE course each from THREE baskets of electives: Theory, Systems, and AI/ML (can be taken in Semester 1 or 2)	3	1	0	0	8	24
1	CS5800	Advanced Data Structures and Algorithms	3	1	0	0	8	12
1	CS6150	Advanced Programming	1	0	0	3	8	12
		Semester 1 Total Credits :						48
		Total Program Credits :						194

Semester 2

Sem	Course No	Course Title	Lecture	Tutorial	Ext. Tut.	Lab	Time outside class	Credits
2	DPE3	ONE course each from THREE baskets of electives: Theory, Systems, and AI/ML	3	1	0	0	8	12
2	DPE4	Dept. Elective 4	3	1	0	0	8	12
2	DPE5	Dept. Elective 5	3	1	0	0	8	12
2	DPE6	Dept. Elective 6	3	1	0	0	8	12
2	DPE7	Dept. Elective 7	3	1	0	0	8	12
		Semester 2 Total Credits :						60
		Total Program Credits :						194

Semester 3

Sem	Course No	Course Title	Lecture	Tutorial	Ext. Tut.	Lab	Time outside class	Credits
3	CS5931	M.Tech Project Phase I (includes 20 summer credits)	0	0	0	0	50	50
		Semester 3 Total Credits :						50
		Total Program Credits :						194

Semester 4

Sem	Course No	Course Title	Lecture	Tutorial	Ext. Tut.	Lab	Time outside class	Credits
4	CS5932	M.Tech Project Phase II	0	0	0	0	36	36
		Semester 4 Total Credits :						36
		Total Program Credits :						194

Notes:

Three course baskets will be broadly defined: Theory, Systems, AI/ML (in other words, every PG course in the department will be part of one of the three baskets).

Each MTech student must credit at least one course from each of the three baskets (also called the “three-basket requirement”). Every student must take* these three courses within the first two semesters.

Project Phase I is a prerequisite for Project Phase II. Project Phase I will be evaluated by a PG committee in the month of November/December (the third semester in the program).

Students who obtain a grade of U, D, or E for Project I will not be permitted to register for Project II. They must register for three Dept. elective courses (equivalent total credits of 36) in lieu of Project II. The total project credits for these students will be 50 credits.

Students who fail in Project I will be required to register for Project I again in the fourth semester and complete it successfully.

For students with CGPA of 6.5 or below at the end of the second semester, the Faculty Advisor and Head of the Dept. may recommend, on a case-by-case basis, that the student register for M.Tech. Project credits of 50 (CS5931) in the fourth semester or later, after completing an additional 36 credits of Dept. electives in the third semester.

Only students who have completed all required courses except at most one course, at the end of the second semester, will be permitted to register for M.Tech. Project Phase-I in the third semester.

Students with more than one uncompleted course must complete all coursework by the end of the third semester and then register for M.Tech. project credits, in consultation with the Faculty Advisor and the Head of the Dept.

*Clarification: The term "take" means "enroll and get a grade for the course." If a student does not get a pass grade in any basket’s course that they “take,” they can complete the backlog (either repeat the same course or another course in that basket) anytime during their MTech program, in order to complete the three-basket requirement towards the degree.

Summary of Changes

Ensuring breadth of courses: one course from each of the three baskets of electives in 1st semester.
One additional course (5th course of 12 credits) in 2nd semester.
Redistribution of MTP I+II credits from 48+48 to 50+36 respectively.

Course Baskets

| Theory Basket

Course ID	Course Name	Course Acronym (if any)
CS5130	Mathematical Tools for Theoretical Computer Science	Toolkit
CS5210	Linear Programming & Combinatorial Optimization	LPCO
CS5666	Foundations of Blockchain Technology
CS5820	Probability and Computing
CS6014	Computability and Complexity	CoCo
CS6025	Sublinear Algorithms
CS6030	Logic and Combinatorics for Computer Science
CS6100	Topics in Algorithm Design and Analysis	TADA
CS6101	Parameterized Algorithms	PA
CS6110	Computational Geometry
CS6111	Foundations of Cryptography
CS6115	Structure versus Hardness in Cryptography
CS6122	Probabilistic and Smoothed Analysis of Algorithms
CS6130	Advanced Graph Algorithms	AGA
CS6170	Randomized Algorithms
CS6190	Recent Developments in Theoretical Computer Science
CS6240	Structural Graph Theory	SGT
CS6535	Matching Theory
CS6741	Algorithmic Foundations of Data Science
CS6840	Modern Complexity Theory	MCT
CS6841	Approximation Algorithms	AA
CS6842	Algorithmic Algebra
CS6845	Pseudorandomness
CS6846	Quantum Algorithms and Quantum Complexity
CS6850	Topics in Complexity Theory	TCT
CS6851	Distributed Algorithms
CS6854	Topics in Distributed Algorithms
CS6858	Distributed Trust
CS7111	Topics in Cryptography
CS7260	Post-Quantum Cryptography

| Systems Basket

Course ID	Course Name	Course Acronym (if any)	Remarks
CS5030	Automated Program Verification	APV	proglang
CS5205	Internet of Things: Protocols and Programming	IOTPP
CS5360	Computer Graphics	CG
CS6013	Modern Compilers - Theory & Practice		proglang
CS6023	GPU Programming		proglang
CS6040	Router Architectures and Algorithms	RAA	networks
CS6045	Software Defined Networking	SDN	networks
CS6120	Wireless Communications and Networks	WCN	networks
CS6210	Performance Evaluation of Computer Systems	PECS
CS6225	Programs and Proofs		proglang
CS6230	CAD for VLSI		vlsi
CS6235	Analysis of Parallel Programs	AOPP	proglang
CS6330	Digital System Testing and Testable Design		vlsi
CS6500	Network Security	NetSec	security
CS6530	Applied Cryptography		security
CS6560	Parallel Computer Architecture	PCA	Arch
CS6570	Secure Systems Engineering	SSE	security
CS6600	Computer Architecture		arch
CS6630	Secure Processor Microarchitecture	SPM	security
CS6650	Smart Sensing for Internet of Things		embedded
CS6666	Blockchain and Distributed Ledger Technologies
CS6720	Data Mining
CS6747	Advanced Wireless Networks
CS6760	Digital Design Verification		vlsi
CS6843	Program Analysis		proglang
CS6844	Advanced Wireless Communications and Networks	AWCN	networks
CS6847	Cloud Computing
CS6848	Principles of Programming Languages	POPL	proglang
CS6852	Theory and Applications of Ontolologies	TAO
CS6868	Concurrent Programming	CP	proglang
CS7030	Recent Topics in Compilers	RTOC	proglang

| AI/ML Basket

Course ID	Course Name	Course Acronym (if any)
CS5011	Machine Learning
CS5020	Non-linear Optimisation : Theory and Algorithms	NLO
CS5691	Pattern Recognition and Machine Learning	PRML
CS6012	Social Network Analysis
CS6015	Linear Algebra and Random Processes	LARP
CS6024	Algorithmic Approaches to Computational Biology	AACB
CS6046	Multi armed Bandits	MAB
CS6250	Memory Based Reasoning in AI
CS6251	Computational Models of Cognition	CMC
CS6300	Speech Technology
CS6350	Computer Vision	CV
CS6360	Computer Graphics	CG
CS6370	Natural Language Processing	NLP
CS6380	Artificial Intelligence
CS6464	Concepts in Startistical Learning Theory	CSLT
CS6515	Stochastic Optimization
CS6680	Planning and Constraint Satisfaction
CS6700	Reinforcement learning
CS6710	Advances in Visual Perception
CS6720	Data Mining
CS6730	Probabilistic Graphical Models	PGM
CS6740	Searching and Indexing in Big Data Sets
CS6770	Knowledge Representation and Reasoning
CS6777	Optimization Methods for Computer Vision Applications
CS6780	Algorithmic Game Theory
CS6790	Geometry and Photometry based Image Formation
CS6870	Digital Video Processing
CS6886	Systems Engineering for Deep Learning
CS6910	Fundamentals of Deep Learning	DL
CS7011	Topics in Reinforcement Learning
CS7012	Multilayer Network Models and Algorithms
CS7016	Topics in Deep Learning
CS7020	Advances in Theory of Deep Learning
CS7370	Causal Inference

| Annexure: List of non-CSE department courses that can be taken as department electives

Sl No.	Course No.	Course Title
1	BT6270	Computational Neuroscience
2	BT5420	Computer Simulations of Biomolecular Systems
3	EE5120	Applied Linear Algebra
4	EE5121	Convex Optimization
5	EE5130	Digital Signal Processing
6	EE5140	Digital Modulation and Coding
7	EE5142	Introduction to Information Theory and Coding
8	EE5154	Complex Network Analytics
9	EE5162	Information Theory
10	EE5170	Speech Signal Processing
11	EE5175	Image Signal Processing
12	EE5176	Computational Photography
13	EE6132	Machine Learning for Computer Vision
14	MA5011	Advanced Graph Theory
15	MA5014	Applied Stochastic Processes
16	MA5015	Number Theory
17	MA5440	Combinatorics and Number Theory
18	MA5850	Operations Research
19	MA5890	Numerical Linear Algebra
20	MA6001	Introduction to Coding Theory
21	MA6005	Applied Linear Algebra
22	MA6190	Mathematical Logic
23	MA6210	Combinatorial Optimization
24	MA6312	Mathematical theory of Games
25	MA6420	Algebraic Theory of Codes and Automata
26	MA6470	Commutative algebra
27	MA6480	Galois theory
28	DA5400	Foundation of Machine Learning
29	DA6300	Quantum Computing and Machine Learning
30	DA6400	Introduction to Reinforcement Learning
31	DA6401	Introduction to Deep Learning
32	DA7450	Topics in AI Privacy