BTech Curriculum - 2020 batch onward

Semester 1 Credits
MA 1110 Calculus - I 1
MA 1220 Calculus - II 1
CY 1017 Environmental Chemistry 2
EP 1108 Modern Physics 2
ID 1063 Intro to Programming 3
SS xxxx English Comm 2
CS 1010 Discrete Math 3
AI 1001 Intro to AI 1
Total 15


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 4 Credits
AI2101 Convex Optimization 3
CS2443 Algorithms 3
AI2100 Deep Learning 3
MAxxxx Applied Statistics 3
CS3320 Compilers - 1 1
CS3563 DBMS - II 3
SSxxxx Intro to Entrepreneurship 1
Total 17


Semester 5 Credits
MA5060 Numerical Analysis 3
CS2323 Computer Architecture 2
AI3000 Reinforcement Learning 3
CS3530 Computer Networks - I 1
CS3510 OS-1 1
AI3001 Advanced Topics in ML 2
EE2102 Control Systems 3
LA xxxx LA/CA Elective 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


Semester 7 Credits
AI Electives (see baskets) 12
LA xxxx LA/CA Elective 1
AI4000 Robotics 3
Total 16


Semester 8 Credits
AI Electives (see baskets) 9
XX xxxx Free Electives 6
LAxxxx Ethics and Values 1
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).

BTech modified curriculum (2019 Batch)

Semester I
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


Semester IV Credits
CS 2443 Algorithms 3
CS 2420 Intro to Complexity Theory 1
CS 3523 OS - II 3
AI 2101 Deep Learning 3
AI 2150 IDP 1
AI 2101 Convex Optimization 3
AI 1100 Artificial Intelligence 2
Total 16


Semester V New credits
AI 4000 Robotics 3
CS3550 DBMS-I 1
AI **** AI Electives (baskets below) 6
CS 3530 Computer Networks-I 1
AI3000 Reinforcement learning 3
LA/CA LA/CA Electives 1
PH / CY Science Elective 1
AI 3050 IDP 1
Total 17


Semester VI Credits
AI 3102 Sequence Models 1
AI **** AI Electives (baskets below) 3
CS 3563 DBMS-II 3
CS 3543 Computer Networks - II 3
FE Free Electives 6
Total 16


Semester VII Credits
AI **** AI Electives (baskets below) 9
PH/CY Science Elective 1
FE **** Free Elective 2
LA/CA LA/CA Electives 2
Total 15


Semester VIII Credits
AI **** AI Electives (baskets below) 8
PH/CY Science Elective 1
LA/CA LA/CA Electives 3
AI 3150 IDP 1
FE Free Electives 2
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).


Semester Total
1 2 3 4 5 6 7 8
AI Core 4 4 10 6 5 3 0 0 32
AI Elec 0 0 0 0 4 6 8 8 26
CS 2 5 5 10 1 3 0 0 26
EE 0 1 0 1 0 0 0 0 2
LA/CA 1 0 0 0 2 1 3 3 10
FE 0 0 0 0 2 2 3 3 10
Sci/MA 5 3 3 0 1 0 1 1 14
ID 5 1 0 0 0 0 0 0 6
Total 16 15 17 17 16 15 15 15 126


Elective Baskets

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