M.Tech. (AI) Curriculum 2023 – 25 Batch onwards

The curriculum of the two-year M.Tech. (AI) programme comprises a total of 64 credits of which 39 credits account for course-work and 25 credits for project work. The course-work is organized as follows:

  • Pool-A courses (Hardcore): 19 credits
  • Pool-B courses (Softcore): Minimum 12 credits
  • Electives: Remaining credits to make a minimum total of 39 course credits

Pool A Courses:

E0 2513:1Data Structures and Algorithms
E1 2223:0Stochastic Models and Applications
E2 2023:0Random Processes
E0 2983:1Linear Algebra and Its Applications
E0 2303:1Computational Methods of Optimization
E1 2133:1Pattern Recognition and Neural Networks
E0 2703:1Machine Learning
E2 2363:1Foundations of Machine Learning
E9 2053:1Machine Learning for Signal Processing

Pool B Courses:

E0 2593:1Data Analytics
E0 2493:1Approximation Algorithms
E0 2353:1Cryptography
E0 2383:1Intelligent Agents
E0 2713:1Graphics and Visualization
E1 2773:1Reinforcement Learning
E1 2163:1Computer Vision
E1 2543:1Game Theory
E1 2413:0Dynamics of Linear Systems
E1 2453:0Online Prediction and Learning
E1 2443:0Detection and Estimation Theory
E1 2012:1Hardware Acceleration and Optimization for Machine Learning
E2 2013:0Information Theory
E2 2313:0Topics in Statistical Methods
E2 2073:0Concentration Inequalities
E9 2412:1Digital Image Processing
E9 2613:1Speech Information Processing
E9 2463:1Advanced Image Processing
E9 2083:1Digital Video: Perception and Algorithms
CP 2143:1Foundations of Robotics
CP 2602:1Perception and Intelligence
DS 2563:1Scalable Systems for Data Science
DS 2653:1Deep Learning for Computer Vision

The remaining credits to make a minimum total of 39 course credits can be taken from among all courses offered in the institute with the approval of the advisor.

AI 299 0:25 Dissertation Project

(Last updated: January 5, 2023)