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.
| Sem. | Course No. | Course Title | Lecture | Tutorial | Ext. Tut. | Lab | Time to be spent outside of 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 |
| 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 |
| 3 | CS5931 | M.Tech Project Phase I (includes 20 summer credits) | 0 | 0 | 0 | 0 | 50 | 50 |
| Semester 3 | Total Credits: | | | | | | 50 |
| 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.
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 |
