IIT Madras Free Machine Learning Course 2026: What to Know
IIT Madras is set to offer a free online course titled “Introduction to Machine Learning” for the January to April 2026 semester. This course, available through the NPTEL/SWAYAM platform, aims to provide a comprehensive understanding of machine learning concepts, backed by mathematical principles.
Course Overview
The “Introduction to Machine Learning” course spans 12 weeks and is designed to cater to serious learners, including students and working professionals. The curriculum covers essential topics such as:
- Probability and Linear Algebra
- Regression Techniques
- Support Vector Machines (SVMs)
- Neural Networks
- Decision Trees and Ensembles
- Clustering Techniques
- Graphical Models
- Basic Reinforcement Learning
The course is taught by Professor Balaraman Ravindran, a distinguished faculty member at IIT Madras, known for his expertise in computer science.
Enrollment Details
Enrollment for the course is free, allowing students to access lectures, notes, and assignments without any cost. However, if learners wish to obtain a formal certificate, they must register for a proctored exam, which incurs a fee of ₹1,000. Here’s a breakdown of what is free and what is paid:
- Free: Course content (videos, assignments, notes, forums)
- Paid: Certification exam (₹1,000) and e-certificate upon passing
This structure provides a low-risk opportunity for learners to explore the course content and decide on certification later.
Key Dates
The 2026 course follows the typical NPTEL semester schedule. Important dates include:
- Course Duration: January 19, 2026 – April 10, 2026
- Enrollment Window: November 17, 2025 – January 26, 2026
- Exam Registration: December 13, 2025 – February 13, 2026
- Exam Date: April 17, 2026 (subject to change)
The exam will be held in a proctored format at designated NPTEL centers across India.
How to Apply
Applying for the course is a straightforward process that can be completed online:
- Visit the official NPTEL course page for “NOC: Introduction to Machine Learning, IIT Madras”.
- Click on “Join”.
- Log in using a Google/Microsoft account or an existing SWAYAM/NPTEL ID.
- Fill in your basic profile information (name, institution, year of study, etc.).
- Confirm your enrollment to access lectures and assignments as per the schedule.
Exam registration for the certification exam will take place later through the NPTEL exam portal.
Who Should Apply?
While the course is categorized as an undergraduate/postgraduate elective in Computer Science and Engineering, it is suitable for a broader audience. Ideal candidates include:
- Senior undergraduate and postgraduate students in Computer Science, Electronics, Electrical, Information Technology, Mathematics, or related fields.
- Working professionals seeking to build a solid foundation in machine learning beyond basic tutorials.
- Researchers from various disciplines (economics, biology, social sciences) who require statistical learning tools.
IIT Madras recommends that learners have a basic understanding of programming and some exposure to probability, linear algebra, and optimization. The course includes a Week 0 recap to help refresh these foundational concepts.
Course Content Structure
The course is designed to be concept-driven, focusing on a mathematically sound introduction to machine learning rather than a quick overview. The first two weeks will revisit fundamental concepts such as probability, linear algebra, and convex optimization. This foundational phase is crucial for helping students understand that machine learning is an extension of statistics and optimization.
From Weeks 2 to 5, the course will delve into classical supervised learning methods, including:
- Linear and Multivariate Regression
- Logistic Regression
- Discriminant Analysis
- Support Vector Machines
- Neural Networks
This structured approach ensures that learners build a robust understanding of machine learning principles over the course duration.
Note: This article provides an overview of the IIT Madras free machine learning course for 2026. For the most accurate and updated information, please refer to the official NPTEL website.
