Department of Artificial Intelligence (AI)

BTech Curriculum - 2020 batch onward

	Semester 2	Credits
EE 1203	Vector Calculus	1
MA1150	Differential Equations	1
MA1230	Series of Functions	1
AI1100	Artificial Intelligence	2
AI1103	Probability and Random Variables	3
ID1054	Digital Fabrication	2
BM1030	Bioengineering	1
ID xxxx	Engineering Electives	1
AI 1104	Programming for AI	1
LA xxxx	LA/CA Elective	3
	Total	16

	Semester 3	Credits
ID2230	Data Structures	3
MAxxxx	Introduction to Metric Spaces	1
AI2000	Foundations of Machine Learning	3
EE2100	Matrix Theory	3
CS3550	DBMS - I	1
EE3900	Linear Systems and Signal processing	3
LA1500	AI and Humanity	1
SSxxxx	Personality Development	1
	Total	16

	Semester 6	Credits
XX xxxx	Free Electives	6
	AI Electives (6 credits can be converted to internship)	9
ID xxxx	Engineering Electives	1
	Total	16

Elective basket “Core AI and ML” (At least 5 credits from the following)
Course name	Credits
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
Introduction to Submodular Functions	1

Elective basket “Language Technologies” (At least 3 credits from the following)
Course name	Credits
Natural Language Processing	3
Information Retrieval	3
Text Processing	3

Elective basket “Speech and Vision” (At least 3 credits from the following)
Course name	Credits
Computer Vision	3
Speech Systems	3
Image and Video Processing	3
Surveillance Video Analytics	3

Elective basket “Data Analytics” (At least 3 credits from following)
Course name	Credits
Predictive Analysis	3
Data Mining	3
Time Series Analysis	1
Graph Analytics for Big Data	3
Distributed Systems	3
Cloud Computing	3
Big Data: Tools and Techniques	1

Elective basket “AI, Neuroscience and Natural Intelligence” (at least 3 credits from the following)
Course name	Credits
Computational Neuroscience lab	2
Brain Machine Interfaces	3
Movement Sciences lab	2
Movement Science and Disorders	3
Theoretical & Computational Neuroscience	2
Applications of AI in Healthcare	1

Out of 30 department electives, 17 must be from the baskets (as specified below). The remaining 13 credits can be any of the remaining basket courses or any CS/EE/MA courses.
At least TWO of these department elective courses must be 3-credit courses.
Six credits of Department Electives in the sixth semester can optionally be converted to a semester long internship in the sixth semester. The onus is on the student to distribute/complete the remaining 11 credits in the sixth semesters in other semesters.
Maximum 4 credit of CA courses, and 6 credits of LA courses can be taken
For most AI courses, the lab component is built into the courses themselves.
Electives not in the lists below can be considered in a given basket with approval of faculty advisor (e.g. a new AI elective offered by a new faculty).

Semester I
C. No.	Course Name	Credits
C. No.	Course Name	Credits
MA 1110	Calculus I	1
MA 1220	Calculus II	2
AI 1001	Introduction to Modern AI	1
AI 1002	Introduction to Drones	1
CS 1310	Discrete Structures I	2
ID 1054	Digital Fabrication	2
ID 1035	Independent Project	1
ID 1303	Introduction to Programming	2
PH /CY	Science Elective	2
LA/CA	Electives	1
	Total	15

Semester II
MA1130	Vector Calculus	1
AI 1101	Linear Algebra	3
AI 1102	Probability and Random Variables	2
MA1150	Differential Equations	1
CS 1340	Discrete Structures II	2
CS1353	Introduction to Data Structures	3
ID 1370	Digital Signal Processing	1
MA2140	Statistics	1
EE1210	Basic Control Theory	1
AI 1150	IDP	1
	Total	16

Semester III		Credits
MA 2120	Transforms	1
AI 2000	Foundations of Machine Learning	3
MA3140	Statistical Inference	3
CS 2400	Principles of Programming Languages I	1
CS 3510	OS-I	1
CS 2323	Computer Architecture	2
AI 2003	Stochastic Processes	1
AI 3002	Introduction to Brain and Neuroscience	1
LA 1500	AI and Humanity	1
AI 2050	IDP	1
	Total	15

Six credits of Free electives in the sixth semester can optionally be converted to a semester long internship in the sixth semester. The onus is on the student to distribute/complete the remaining 11 credits in the sixth semesters in the other semesters.
Electives not in the given basket lists can be considered in a given basket with approval of faculty advisor (e.g. a new AI elective offered by a new faculty).

Core AI and ML (At least 6 credits from the following)
Statistical Learning Theory
Kernel Methods for Machine Learning
Optimization Methods in Machine Learning
Bayesian Data Analysis
Numerical Linear Algebra
Information Theory and Coding
Representation Learning
Introduction to Submodular Functions

Speech and Vision (At least 6 credits from the following)
Computer Vision
Speech Systems
Image and Video Processing

Language Technologies (At least 5 credits from the following)
Natural Language processing
Information Retrieval
Text processing

Data Analytics (At least 3 credits from following)
Predictive Analysis
Data Mining
Time Series Analysis
Graph Analytics for Big Data
Distributed Systems
Cloud Computing
Big Data: Tools and Techniques

Emerging Technologies (At least 2 credits from following)
Principles of Cyber Security
Computer Forensics
Bitcoins and Cryptocurrencies
Cryptography
Randomized Algorithms
Quantum Computing

AI, Health and Humans (At least 2 credits from following)
Bioinformatics
Gene Editing
Applications of AI in Healthcare
Theoretical and Computational Neuroscience
Neuromechanics
Natural Intelligence

Smart Industry (At least 2 credits from the following)
Computer Integrated Manufacturing
Machine Diagnostics and Condition Monitoring
Mathematical Elements of Geometrical Modeling