Postgraduate

M.Tech Curriculum

Our Master’s program provides rigorous training in both theoretical foundations and practical applications of Artificial Intelligence.

Programs offered include the 2-year M.Tech, the 3-year M.Tech R.A (July admission), and the 3-year M.Tech R.A (January admission).

Either the Advanced or Regular version can be taken where applicable.

Year	Odd Semester			Even Semester
Year	Course Code	Course Name	Credits	Course Code	Course Name	Credits
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
	AI5000	Foundations of Machine Learning	3	AI5016	Industry Lecture series	1
	EE5609	Matrix Theory	3		AI Electives	9
	CS6013 /ID2230	Data Structures & Applications*	3
	LA5180	Communication Skills : Advanced	1
			Total	13		Total	13
Summer	AI6105	Thesis Stage - I	3
Summer Total	3
2	AI6205	Thesis stage – II	9	AI6305	Thesis stage – III	12
		Total	9		Total	12

Year	Odd Semester	Even Semester
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
AI5000	Foundations of Machine Learning	3	AI5016	Industry Lecture series	1
EE5609	Matrix Theory	3		AI Electives (See Below)	6
LA5180	Communication Skills : Advanced	1
		Total	10		Total	10
2	AI6115	Thesis Stage - I	3	AI6215	Thesis stage – II	6
CS6013	Advanced Data Structures & Applications	3
	AI Electives (See Below)	3
		Total	9		Total	6
3	AI6315	Thesis stage – III	6	AI6415	Thesis stage – IV	9
		Total	6		Total	9

Year	Odd Semester	Even Semester
1	AI5030	Probability and Stochastic Processes	3	AI5100	Deep Learning	3
AI5000	Foundations of Machine Learning	3	EE5609	Matrix Theory	3
	AI Electives (See Below)	3	CS6013	Advanced Data Structures & Applications	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 (See Below)	6
		Total	9		Total	6
3	AI6315	Thesis stage – III	6	AI6415	Thesis stage – IV	9
		Total	6		Total	9

Course Code	Course Name
AI3102	Sequence models
AI5040	Game Theory and Mechanism Design
AI5120	Explainability in ML
AI5153	Mobile Robotics
AI5133	AI and sensors
AI5090	Stochastic Processes and Applications
AI5073	Neuromorphic Artificial Intelligence
AI3603/CS5290	Computer Vision
	Reinforcement Learning
	Convex Optimization
	Natural Language Processing
	Artificial Intelligence
	Generative Artificial Intelligence
CS6170	Computer Vision for Autonomous Vehicle Technology
CS5300	Parallel & Concurrent Programming
CS5350	Bayesian Data Analysis
CS6370	Information Retrieval
CS5700	Text processing and Retrieval
CS6870	Surveillance Video Analytics, Visual Big data analytics, Video content analysis
CS6140	Video Content Analysis
CS5600	Data Mining
CS6460	Visual Big Data Analytics
CS5320	Distributed Computing
CS6430	Stochastic Processes in Machine Learning
HT5030	Brain & Neuroscience
EE5604	Intro to Statistical Learning theory
EE5605	Kernel Methods for ML
EE5470	Nonlinear Control Techniques
EE5903	Information Theory, Coding and Inference
EE5328	Introduction to Submodular Functions
EE6307	Speech Systems