IIT Madras Offers Free Online Course on Machine Learning in English and Tamil
IIT Madras has offered a Free Online Course on Machine Learning for English and Hindi Students on NPTEL Platform
IIT Madras is currently accepting applications for a free online course called Introduction to Machine Learning which can be taken by students and professionals. The course is offered in both English and Tamil, and while the English course lasts 12 weeks, the Tamil course is shorter and can be completed in 4 weeks. After successfully completing the course and homework, participants can obtain a certificate by paying Rs 1000 and passing an exam to be held on April 24, 2022 for the English course and March 27, 2022 for the Tamil course.
The free online machine learning course in English will be led by Balaraman Ravindran who is currently Professor of Computer Science at IIT Madras and a Mindtree faculty member. He has nearly two decades of experience in machine learning research and specifically reinforcement learning. The Tamil course will be led by Arun Rajkumar who is currently an Assistant Professor in the Department of Computer Engineering at IIT Madras. His PhD thesis was on machine learning and his major research interests are in machine learning and sequential decision making.
Who can take the IIT Madras Free Online Course on Machine Learning?
The courts can be occupied by teachers and undergraduate and postgraduate students with a basic knowledge of linear algebra, probability, programming and algorithms. The objective of the course is to cover the topics at a high level so that it acts as a first course for a full-fledged machine learning course. As for the Tamil course, the course will be conducted in spoken Tamil while the technical terms covered, exams or assignments will be in English.
What will IIT Madras Free Online Course on Machine Learning Cover?
The course will cover the different learning paradigms and some of the most popular algorithms and architectures used in machine learning. The course in English will cover the following topics:
Probability theory, linear algebra and convex optimization.
Introduction: Statistical decision theory, regression, classification or bias variance.
Linear regression, multivariate regression, subset selection, reduction methods, principal component regression and partial least squares.
Decision trees, regression trees, stopping criteria and pruning loss functions, categorical attributes, multiple splits, missing values, decision trees – jitter evaluation metrics, and much more.
The course is Tamil will cover the following topics:
- Introduction to Supervised Learning – Regression; Topics – Linear regression; peak regression; LASSO.
- Supervised learning – Classification; Topics: K-NN, Decision Tree, Naive Bayes, Logistic Regression.
- Supervised learning – Classification; Topics: Perceptron, Support Vector Machines, Introduction to Neural Networks.
- Unsupervised learning – K-means Clustering, PCA