M.Tech Curriculum

Curriculum for M.Tech (2 Years)
Year	Odd Semester		Credits	Even Semester		Credits
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
	AI5000	Foundations of Machine Learning	3	AI5120	Topics in Optimization	3
	AI5110	Linear Algebra and Applications	3		AI Electives**	6
		AI Elective **	3	AI 5016	Industry Lecture series *	1
	LA 5180	Communication Skills: Advanced *	1
	Total		13	Total		13
Summer	AI6105	Thesis Stage - I				3
Summer	Summer Total					3
2	AI6205	Thesis stage – II	9	AI6305	Thesis stage – III	12
2	Total		9	Total		12

*Communication Skills and *Industry lecture series may be taken either in sem 1 or sem 2 depending on the availability.
** Department electives can be completed within the first 3 semesters.
Electives not in the given lists can be considered with approval of faculty advisor and DPGC (e.g. a new AI elective offered by a new faculty).
The above displayed curriculum is effective July 2026 onwards.

Curriculum for M.Tech R.A (July Admission)
Year	Odd Semester		Credits	Even Semester		Credits
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
	AI5000	Foundations of Machine Learning	3	AI5120	Topics in Optimization	3
	AI5110	Linear Algebra and Applications	3		AI Electives **	3
	LA5180	Communication Skills : Advanced *	1	AI5016	Industry Lecture series *	1
	Total		10	Total		10
2	AI6115	Thesis Stage - I	3	AI6215	Thesis stage – II	6
		AI Electives **	6
	Total		9	Total		6
3	AI6315	Thesis stage – III	6	AI6415	Thesis stage – IV	9
3	Total		6	Total		9

*Communication Skills and *Industry lecture series may be taken either in sem 1 and sem 2 depending on the availability.
**Department electives can be completed within the first 4 semesters.
Electives not in the given basket lists can be considered with approval of faculty advisor and DPGC (e.g. a new AI elective offered by a new faculty).
The above displayed curriculum is effective July 2026 onwards.

Curriculum for M.Tech R.A (Jan Admission)
Year	Odd Semester		Credits	Even Semester		Credits
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
	AI5000	Foundations of Machine Learning	3	AI5110	Linear Algebra and Applications	3
	AI5120	Topics in Optimization	3		AI Electives **	3
	LA5180	Communication Skills : Advanced *	1	AI5016	Industry Lecture series *	1
	Total		10	Total		10
2	AI6115	Thesis Stage - I	3	AI6215	Thesis stage – II	6
		AI Electives **	6
	Total		9	Total		6
3	AI6315	Thesis stage – III	6	AI6415	Thesis stage – IV	9
3	Total		6	Total		9

*Communication Skills and *Industry lecture series may be taken either in sem 1 and sem 2 depending on the availability.
**Department electives can be completed within the first 4 semesters.
Electives not in the given lists can be considered with approval of faculty advisor and DPGC (e.g. a new AI elective offered by a new faculty).
The above displayed curriculum is effective July 2026 onwards.

Elective List
Course Name	Credits
Intro to Statistical Learning Theory	1
Kernel Methods	1
Sequence Models	1
Brain and Neuroscience	1
Optimization Methods in Machine Learning / Convex Optimization	3
Bayesian Data Analysis	2
Nonlinear Control Techniques	3
Information Theory and Coding	3
Stochastic Processes for Machine Learning	1
Introduction to Submodular Functions	1
Artificial Intelligence	2
Natural Language Processing	3
Information Retrieval	3
Text Processing	3
Data Mining	3
Computer Vision	3
Speech Systems	3
Image and Video Processing	3
Surveillance Video Analytics, Visual Big Data Analytics, Video Content Analysis	3
Computer Vision for Autonomous Vehicle Technology	3
Parallel & Concurrent Programming	3
Distributed Computing	3
An Overview of Reinforcement Learning	3
Game Theory and Mechanism Design	3
Neuromorphic Artificial Intelligence	3
Explainability in Machine Learning	3
AI and Sensors	3
Mobile Robotics	3
Cybersecurity and AI	2
Stochastic Processes and Applications	3
Generative Artificial Intelligence	3

Electives