B.Tech Minor in AI & ML Curriculum (12 credits)

Students have to finish a total of 12 credits, with at least one course from each of the following categories (rows). If a student has already completed some of these categories as part of the regular B.Tech Program, the student should take an equivalent number of elective credits to compensate.

AI2000 (or) AI5000 (or) CS5590 (or) CS3390 (or) EE2802Foundations of Machine Learning
AI2100 (or) AI5100Deep Learning
AI3001Advanced Topics in ML
List belowElectives

Electives List

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)

AI and ML: Theory
Probabilistic Graphical Models
Statistical Learning Theory
Kernel Methods
Optimization Methods in Machine Learning
Convex Optimization
Reinforcement Learning
Artificial Intelligence
Bayesian Data Analysis
Representation Learning

Applied AI and ML
Computer Vision
Natural Language Processing
Speech Systems
Image and Video Processing
Data Analytics/Big Data
Applications of AI in Healthcare
Hardware Architectures for Machine Learning
Data Mining
Information Retrieval
AI for Humanity