Overview

• Provide rigorous mathematical background with practical use-cases in machine learning in order to apply classroom concepts to real-world machine learning applications.
• Provide enhanced programming skills to attract relevant (Machine learning based) industry partners for placements.
• Emphasize on collaborations/internships with industry partners and academic laboratories in India and abroad, and Indian NGO/Government agencies.
• To Equip our students with theoretical and practical tools essential for the new-age signal processing and machine learning applications.
• Leverage on the mathematical strengths of an incoming M.Tech. and focus on providing fundamentals pertaining to Machine Learning and advanced signal processing.
• Develop strong programming skills essential for real - world problems.

(Students are also advised to go through the M.Tech. (ECE) specific regulation and PG Regulations to know other requirement of the M.Tech. degree)

For "M.Tech. in ECE with specialization in ML" the student must:

1. Complete the following core courses of the specialization area.
   • Machine Learning OR Statistical Machine Learning
   • Probability and Random Processes
   • Applied Optimization Methods for Machine Learning
2. If opted for Thesis/Scholarly paper, it should be in the specialization domain. The advisor will certify this fact.
3. At least 4 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with Thesis option” .
4. At least 12 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with scholarly paper (8 credit) option” .
5. At least 16 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. with scholarly paper (4 credit) option” .
6. At least 20 credits should be from specialization electives in addition to the core courses, if opted for “M.Tech. without thesis and scholarly paper option” .