M.Tech 3 Years | Department of Artificial Intelligence (AI) - IIT Hyderabad

M.Tech (3 yr) AI curriculum (Jan admission, applicable from Jan 2021)

Semester 1		Credits
AI5030	Probability and Stochastic Process	3
AI5100	Deep Learning	3
	AI Electives	3
LA5180	Communication Skills : Advanced	1
	Total	9

Semester 2		Credits
AI5000	Foundations of Machine Learning	3
EE5609	Matrix Theory	3
CS6013/ ID2230	Advanced Data Structures and Algorithms/ Data Structures & Applications	3
AI5016	Industry Lecture series	1
	Total	10

Semester 3		Credits
AI6115	Thesis stage - I	3
	AI Electives (baskets below)	6
	Total	9

Semester 4		Credits
AI6215	Thesis stage - II	6
	AI Electives (baskets below)	1
	Total	7

Semester 5		Credits
AI6315	Thesis stage - III	6
	Total	6

Semester 6		Credits
AI6415	Thesis stage - IV	9
	Total	9

Electives Basket

"Core AI and ML" (At least 4 credits from the following)
Probabilistic Graphical Models
Statistical Learning Theory
Kernel Methods
Stochastic Processes/Probability Models-II
Artificial Intelligence
Reinforcement Learning
Bayesian Data Analysis
Optimization Methods in Machine Learning
Convex Optimization
Representation Learning
Stochastic Processes for Machine Learning
Introduction to Submodular Functions

"Language technologies" (At least 3 credits from the following)
Natural Language processing
Information Retrieval
Text processing
Data Mining

"Speech and Vision" (At least 4 credits from the following)
Computer Vision
Speech Systems
Image and Video Processing
Surveillance Video Analytics
Computer Vision for Autonomous vehicles

Category wise split	Credits
Department Electives	10
Department Core	14
Thesis	24
Total	48
Soft Skills	2

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 any semester, within the first 2 years
Electives not in the given lists can be considered with approval of faculty advisor/DPGC (e.g. a new AI elective offered by a new faculty).

MTech (3 yr) curriculum (2020 Batch onward, July admission)

Semester 1		Credits
AI5002	Probability and Stochastic Processes	3
AI5000	Basics of Machine Learning	3
EE5609	Matrix Theory	3
SSxxxx	Communication Skills: Advanced	1
	Total	9

Semester 2		Credits
AI5100	Deep Learning	3
	AI Electives (baskets below)	6
Ai5006	Industry Lecture Series	1
	Total	10

Semester 3		Credits
AI6110	Thesis Stage - I	3
CS6013	Advanced Data Structures and Algorithms	3
	AI Electives (baskets below)	3
	Total	9

Semester 4		Credits
AI6210	Thesis stage - II	6
	AI Electives (baskets below)	1
	Total	7

Semester 5		Credits
AI6310	Thesis stage - III	6
	Total	6

Semester 6		Credits
AI6410	Thesis stage - IV	6
	Total	6

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 any semester, within the first 2 years
Electives not in the given lists can be considered with approval of faculty advisor/DPGC (e.g. a new AI elective offered by a new faculty).

Electives Basket

"Core AI and ML" (At least 4 credits from the following)
Intro to Statistical Learning Theory	1
Kernel Methods	1
Sequence Models
Optimization Methods in Machine Learning/Convex Optimization - II	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

"Language technologies" (At least 3 credits from the following)
Natural Language processing	3
Information Retrieval	3
Text processing	3

"Speech and Vision" (At least 3 credits from the following)
Computer Vision
Speech Systems
Image and Video Processing
Surveillance Video Analytics

MTech Curriculum (3 year, August 2022)

Semester 1		Credits
AI5030	Probability and Stochastic Processes	3
EE5609	Matrix Theory	3
AI5000	Foundations of Machine Learning	3
EE5602	Communication Skills: Advanced*	1
	Total	10

Semester 2		Credits
AI5100	Deep Learning	3
	AI Electives	6
AI5016	Industry Lecture Series*	1
	Total	10

Semester 3		Credits
AI6115	Thesis Stage - I	3
CS6013/ID2230	Advanced Data Structures and Algorithms/ Data Structures and Applications	3
	AI Electives	3
	Total	9

Semester 4		Credits
AI6215	M.Tech Thesis Stage - II	6
	Total	6

Semester 5		Credits
AI6315	M.Tech Thesis Stage - III	6
	Total	6

Semester 6		Credits
AI6415	M.Tech Thesis Stage - IV	9
	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 any semester, within the first 2 years
Electives not in the given lists can be considered with approval of faculty advisor/DPGC (e.g. a new AI elective offered by a new faculty).

AI Electives

Course	Credits
Intro to Statistical Learning Theory	1
Kernel Methods	1
Sequence Models	1
Bayesian Data Analysis	1
Non-linear Control Techniques	1
Optimisation Methods in Machine Learning/Convex Optimization	3
Information Theory and Coding	3
Stochastic Processes for Machine Learning	1
Introduction to Submodular Functions	1
Artificial Intelligence	2

Course	Credits
Information Retrieval	3
Natural Language processing	3
Data Mining	3
Text Processing	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