M.Tech. (Online) in AIML

Intelligent Systems

Artificial Intelligence and Machine Learning (AIML) are transforming industries worldwide, from healthcare and finance to e-commerce and smart cities. The M.Tech. (Online) in Artificial Intelligence and Machine Learning is designed to equip students and professionals with advanced knowledge in AI and ML. The curriculum blends foundational theory with modern computational and analytical techniques, enabling participants to develop intelligent systems and address real-world technological challenges. The program emphasizes hands-on training in programming frameworks and tools such as Python, machine learning libraries, and data platforms, ensuring participants build strong practical skills in designing, analyzing, and deploying AI-driven solutions.

Banner
Message from the Department

Curriculum Template

Programme Curriculum
Total Credits
144
9 credits/course
Core Courses
6
54 credits
Elective Courses
6
54 credits
Project
1
36 credits

Courses Offered

Project Credits: 36
Project
ECO921E
Elective Credits: 9
Economics and Governance of AI
Prerequisites: Basic Economics and interest in technology/ policy
IS901E
Core Credits: 9
Introduction to Python and Agentic AI
Prerequisites: None
IS902E
Core Credits: 9
Linear Algebra
Prerequisites: None
IS903E
Core Credits: 9
Introduction to ML
Prerequisites: None
IS904E
Core Credits: 9
Probability and Statistics for ML
Prerequisites: None
IS905E
Core Credits: 9
Optimization and Deep Learning
Prerequisites: None
IS906E
Core Credits: 9
Human-Computer Interaction
Prerequisites: None
IS907E
Elective Credits: 9
AIML Projects with Real-World Datasets
Prerequisites: None
IS908E
Elective Credits: 9
Unsupervised Learning
Prerequisites: None
IS909E
Elective Credits: 9
Ethics of Artificial Intelligence
Prerequisites: Basic understanding of Machine learning is desirable
IS910E
Elective Credits: 9
Big Data Science and Visual Analytics
Prerequisites: Linear Algebra, Probability and Statistics. Introductory Knowledge in Machine Learning will be beneficial.
Students' Preference
Elective Credits: 9
Open Elective

Eligibility Criteria

  • Minimum CPI 5.5 or 55% marks in the qualifying degree

  • A valid score above department-stated cut-off in approved national level exams as applicable to the program discipline (GATE)

or

  • Four-year Bachelor’s degree in Engineering, Science, Economics, or allied areas/ Five-year M.Sc. in Science or allied areas/ PG degrees (MCA/ MA) in Science, Mathematics, or allied areas.
  • Department-conducted written test on basic mathematics.

  • Professionals with over 5 years of relevant experience as defined by the concerned department.
  • Applicants with valid national-level test scores above the department- specified cut off.
  • Candidates nominated* by government/ defense/ other recognized organizations.

* Note: Nominated includes sponsored candidates

Program Fee

f

Certificate Format

degree format Click to enlarge

Instructors

Dr. Ketan Rajawat
Research Interest:

Optimization algorithms in communications, Dynamic network measurement and cartography, Network Localization, Network Optimization

Dr. Aditya Jagannatham
Research Interest:

5G and 6G Wireless Technologies, OTFS Modulation, Terahertz (THz) Communication, Visible Light Communication (VLC), & related areas

Dr. Hamim Zafar
Research Interest:

Computational Biology, Machine Learning and Bioinformatics

Dr. Nitin Saxena
Research Interest:

Computational Complexity Theory, Algebra, Algebraic Geometry, Theoretical Computer Science and Algorithms

Dr. Vimal Kumar
Research Interest:

Political Economics and Game Theory

Dr. Sayak Roy Chowdhury
Research Interest:

Reinforcement Learning, Multi-armed bandits, Differential Privacy and Language Model Alignment

Dr. Sruti Raghavan
Research Interest:

Human-Computer Interaction, Software Engineering, End user Programming, Education and Societal and Humanistic Aspects of Computation

Dr. Sushruth Ravish
Research Interest:

Moral epistemology, Metaethics, Normative ethics, Social epistemology, Political philosophy, Ethics of AI

Dr. Soumya Dutta
Research Interest:

Machine Learning, Visual Computing and Image Analysis, Big Data Visualization and Analytics, Data Science, HPC, Uncertainty Quantification, Explainability and Interpretability of AI Models.

Dr. Tushar Sandhan
Research Interest:

Signal Processing, Computer Vision, Machine Learning, Data science and Pattern Recognition, AI and non-invasive systems

Program FAQ

General Questions

Anyone with a relevant bachelor's degree and minimum 55% marks or 5.5 CPI can apply. Specializations vary across departments but are designed to be interdisciplinary and industry-relevant, with electives across domains.

You can complete the program in 2 to 4 years, at a self-paced schedule.

The total fee is approximately ₹10.77 lakhs, including course, exam, and trimester fees.

Yes. You can pursue either a research (thesis) track or an industry-oriented (project) track. Depending on the department.


 

Questions for Career and Alumni

Yes. Graduates of these programs become part of the prestigious IIT Kanpur alumni network — a global community of innovators and leaders.

They offer industry-relevant curriculum, flexible learning, and credentials from one of India’s top institutes — helping boost both technical expertise and career growth.