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 251 3:1 Data Structures and Algorithms
E1 222 3:0 Stochastic Models and Applications
(or)
E2 202 3:0 Random Processes
E0 298 3:1 Linear Algebra and Its Applications
E0 230 3:1 Computational Methods of Optimization
E1 213 3:1 Pattern Recognition and Neural Networks
(or)
E0 270 3:1 Machine Learning
(or)
E2 236 3:1 Foundations of Machine Learning
(or)
E9 205 3:1 Machine Learning for Signal Processing

Pool B Courses:

E0 259 3:1 Data Analytics
E0 249 3:1 Approximation Algorithms
E0 235 3:1 Cryptography
E0 238 3:1 Intelligent Agents
E0 271 3:1 Graphics and Visualization
E1 277 3:1 Reinforcement Learning
E1 216 3:1 Computer Vision
E1 254 3:1 Game Theory
E1 241 3:0 Dynamics of Linear Systems
E1 245 3:0 Online Prediction and Learning
E1 244 3:0 Detection and Estimation Theory
E1 201 2:1 Hardware Acceleration and Optimization for Machine Learning
E2 201 3:0 Information Theory
E2 231 3:0 Topics in Statistical Methods
E2 207 3:0 Concentration Inequalities
E9 241 2:1 Digital Image Processing
E9 261 3:1 Speech Information Processing
E9 246 3:1 Advanced Image Processing
E9 208 3:1 Digital Video: Perception and Algorithms
CP 214 3:1 Foundations of Robotics
CP 260 2:1 Perception and Intelligence
DS 256 3:1 Scalable Systems for Data Science
DS 265 3:1 Deep Learning for Computer Vision

Electives:
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.

Project
AI 299 0:25 Dissertation Project

 

(Last updated: January 5, 2023)

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