M.Tech Programme · EE2 · Electrical Engineering · IIT Bombay

Control & Computing

Credit Structure

Course Type	Sem 1	Sem 2	Sem 3	Sem 4	Range / Total
Core Courses	18	18	0	0	36
Elective	6	6	6-0	0-6	18
Institute Elective	0	0	0-6*	6-0*	6
Courses outside dept.	0	0	0	0	0
Lab Courses	0	6	0	0	6
Seminar	4	0	0	0	4
R&D Project	0	0	0	0	0
Communication (P/NP)	+6	0	0	0	6
Training (P/NP)	0	0	0	0	0
Course Total	28+6	30	6-12	6-0	70+6
Project	0	42	0	48	90
Total Credits	28+6	72	6-12	48-54	160+6

Total: 34 credits

Course Code	Course Name	L	T	P	C
EE659	First Course in Optimization	3	0	0	6
EE635	Applied Linear Algebra	3	0	0	6
EE640	Multivariable Control Systems	3	0	0	6
EE694	Seminar	0	0	0	4
EE899	Communication Skills	0	0	0	6
—	Elective 1	—	—	—	6
Total					34

Total: 72 credits

Course Code	Course Name	L	T	P	C
EE613	Nonlinear Dynamical Systems	3	0	0	6
EE622	Optimal Control Systems	3	0	0	6
EE636	Matrix Computations	3	0	0	6
EE615	Control and Computation Laboratory	3	0	0	6
EE797	Project Stage 1	—	—	—	42
—	Elective 2	—	—	—	6
Total					72

Total: 6 credits

Course Code	Course Name	C
—	Elective 3 and/or Institute Elective	6
Total		6

Total: 54 credits

Course Code	Course Name	C
EE798	Project Stage 2	48
—	Elective 3 and/or Institute Elective	6
Total		54

#	Course Code	Course Name	C
1	EE714	Behavioural Theory of Systems	6
2	EE603	Digital Signal Processing & its Applications	6
3	EE605	Error Correcting Codes	6
4	EE649	Finite Fields and its Applications	6
5	EE601	Statistical Signal Analysis	6
6	EE677	Foundation of VLSI CAD	6
7	EE725	Computational Electromagnetics	6
8	EE749	Decentralized Control of Complex Systems	6
9	EE763	Science of Information, Statistics & Learning	6
10	EE759	Applied Mathematical Analysis in Engineering	6
11	EE736	Introduction to Stochastic Optimization	6
12	EE6111	Robust Control	6
13	EE608	Adaptive Signal Processing	6
14	EE638	Estimation and Identification	6
15	EE621	Markov Chains & Queuing System	6
16	EE678	Wavelets	6
17	EE720	An Introduction to Number Theory and Cryptography	6
18	EE734	Advanced Probability for random processes for engineers	6
19	EE793	Topics in Cryptology	6
20	EE465	Cryptocurrency and Blockchain Technologies	6
21	EE656	Electrical Machine Analysis and Control	6
22	EE658	Power System Dynamics and Control	6
23	EE708	Information Theory and Coding	6
24	EE710	Large Sparse Matrix Computations	6
25	EE717	Advanced Computing for Electrical Engineers	6
26	EE732	Combinatorial Optimization	6
27	EE737	Introduction to Stochastic Control	6
28	EE739	Processor Design	6
29	EE760	Advanced Network Analysis	6
30	EE779	Advanced Topics in Signal Processing	6

Students can choose at most one course from each set.

Set 1

AE700	Guidance and control of unmanned autonomous vehicles
SC627	Motion planning and coordination of autonomous vehicles
AE713	Space flight dynamics
AE688	Navigation of Autonomous Vehicles
AE686	Guidance of Aerospace Vehicles
CL625	Process Modelling and Identification
CL647	Advanced Process Optimization
CL686	Advanced Process Control
CL701	Computational Methods in Chemical Engineering

Set 2

Set 3

CS725	Foundations of Machine Learning
EE769	Introduction to Machine learning

Set 4

CS791	Probabilistic foundations of AI (previously CS726)
EE782	Advanced topics in machine learning
CS745	Principles of Data and System Security
EE603	Digital Signal Processing and Applications
EE605	Error Correcting Codes
EE608	Adaptive Signal Processing
EE6111	Robust Control

Set 5

EE638	Estimation and Identification
SC612	Introduction to Linear Filtering and Beyond
CL653	State Estimation Theory and Applications

Set 6

CS747	Foundations of Intelligent and Learning Agents
EE736	Introduction to Stochastic Optimization
IE708	Markov Decision Processes

Set 7

IE616	Decision Analysis and Game Theory
SC631	Games and Information
IE718	Networks Games and Algorithms
CS6001	Game Theory and Algorithmic Mechanism Design
IE716	Integer Programming: Theory and Computations
IE804	Convex Analysis
ME604	Robotics
ME766	High Performance Scientific Computing
SC617	Adaptive Control Theory
SC645	Intelligent Feedback and Control

Set 8

SI419	Combinatorics
CS604	Combinatorics

Notes

→ The thesis must lead to work of reputably publishable, patentable, or deployable quality.

→ Any course above 5xx level offered at IITB can be considered as an elective with faculty advisor approval.

→ The Institute Elective (6 credits) can be taken either in the 3rd or 4th Semester.