IIT Madras is offering a free online course on machine learning for students on the National Program on Technology Enhanced Learning
IIT Madras is offering a free online course on introduction to machine learning for students and interested professionals on the SWAYAM NPTEL platform. The course, which is around 12 weeks long, will introduce participants to some of the basic concepts of machine learning from a mathematically well motivated perspective. The different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms will be covered.
The course will be taken by Balaraman Ravindran who is currently a professor in computer science at IIT Madras and also a Mindtree Faculty Fellow . He has nearly two decades of research experience in machine learning and specifically reinforcement learning. His current research interests are centered on learning from and through interactions and span the areas of data mining, social network analysis, and reinforcement learning.
Who Can Take the IIT Madras Free Online Course on Machine Learning?
While anyone interested can take the course, it is an elective subject that is intended for undergraduate and postgraduate students pursuing their BE, ME, MS or PhD. It is most suitable for students pursuing degrees in the following subjects:
- Computer science and engineering.
- Artificial intelligence.
- Data science.
“We will assume that the students know programming for some of the assignments.If the students have done introductory courses on probability theory and linear algebra it would be helpful. We will review some of the basic topics in the first two weeks as well,” says the NPTEL website.
What the IIT Madras Free Online Course on Machine Learning Will Cover?
Some of the topics that will be covered under the course are as follows:
- Probability theory, linear algebra, and convex optimization.
- Introduction: Statistical decision theory, regression, classification, or bias variance.
- Linear regression, multivariate regression, subset selection, shrinkage methods, principal component regression, and partial least squares.
- Decision trees, regression trees, stopping criterion and pruning loss functions, categorical attributes, multiway splits, missing values, decision trees – instability evaluation measures.
- Neural Networks: Introduction, early models, perceptron learning, backpropagation, initialization, training and validation, parameter estimation, MLE, MAP, and Bayesian estimation.
- Bootstrapping and cross validation, class evaluation measures, ROC curve, MDL, ensemble methods – bagging, committee machines and stacking, boosting, and much more.
How to Enroll and Other Important Details
Interested students will have to enroll in the course before 1 August 2022. The course is free to enroll and learn from; however, those who require certificates will have to pay Rs 1000 and take an examination that will be conducted on 29 October 2022. Interested participants may enroll for the course on the official page by using their Facebook, Microsoft, Google or Facebook accounts.