IIT Kharagpur Admission 2022: Admission to Free Online Machine Learning Programme Begins; Apply by August 1

New Delhi: IIT Kharagpur is inviting applications for free machine learning course for undergraduate, postgraduate and research students. The last date to enroll for the course is August 1, 2022.

IIT Kharagpur has started accepting applications for its free online machine learning course on NPTEL. IIT Kharagpur's Machine Learning for Earth System Sciences course is worth two credits. The free machine learning course offered by IIT Kharagpur is appropriate for UG, PG and PhD students. Participants will receive certificates after completing a free online course on the NPTEL website, but they will have to pay INR 1,000 to take an examination. 

IIT Kharagpur Online on machine learning Program 2022: Highlights

IIT Kharagpur Online Machine Learning 2022: Dates

From July 25 through September 16, 2022, IIT Kharagpur will provide a free online course on machine learning. The course will close for enrollment on August 1, 2022. 

The free online course on machine learning will be conducted by Adway Mitra who is an assistant professor at the Center of Excellence in Artificial Intelligence at IIT Kharagpur. The professor works in the domain of machine learning and its applications in climate, remote sensing and modeling of physical processes. He designed and launched the course “Machine Learning for Earth System Sciences” in IIT Kharagpur, that is offered in every Spring Semester since 2020, says the NPTEL website 

The course will begin with a revision of relevant concepts of spatio-temporal statistics and data mining, following which it will take up the topics of earth system observations, earth system data analytics and earth system modeling in various domains, such as hydrology, climate and soil. Some of the topics that will be covered as part of the course are as follows: 

• Recap of probability, and spatio-temporal statistics. 
• Recap of relevant machine learning and deep learning techniques. 
• Earth system process understanding, and case studies related to the same. 
• Earth system modeling, and relevant concepts and applications in different domains. 

IIT Kharagpur Online Machine Learning 2022: Eligibility

IIT Kharagpur's free online course is most suitable for undergraduate, postgraduate and research students pursuing computer science and engineering. Participants are also expected to have knowledge in the following domains: 

• Machine learning. 
• Deep learning. 
• A working idea of one or two domains in earth system sciences. 

Candidates who receive a 25 percent average of the best 6 assignments out of a total of 8 assignments and a 75 percent proctored certification exam score out of 100 will receive e-certificates with the NPTEL and IIT Kharagpur logos. 

IIT Kharagpur Online Machine Learning 2022: How to Apply?

Before August 2, 2021, interested Participants must first sign into the SWAYAM NPTEL portal with their Microsoft, Facebook, or Google accounts before proceeding. There is also the option of logging in using your SWAYAM account. 

SWAYAM accounts are formed by registering with the platform and providing a username, password, and email address, followed by verification of the account. In terms of the course certificate, announcements will be made when the registration form is open for submission, and the online registration form must then be filled out and the certification exam price paid.

IIT Kharagpur Online Machine Learning 2022: Course Layout

Here is a brief layout of the course structure: 

Week 1: Recap of probability, spatio-temporal statistics (autoregression, geostatistical equation, Gaussian Processes, Extreme value statistics)

Week 2: Recap of relevant Machine Learning and Deep Learning techniques (Bayesian Networks, CNN, RNN/LSTM, VaE, Interpretability, Causality)

Week 3: Earth System Process Understanding: case studies (predictors of monsoon, extreme weather forecasting, climate change visualization)

Week 4: Earth System Process Understanding: case studies(Extreme event analysis, networks and teleconnections, causal analysis)

Week 5: Earth System Process Understanding: case studies(Extreme event analysis, networks and teleconnections, causal analysis)

Week 6: Earth System Process Understanding: case studies(Extreme event analysis, networks and teleconnections, causal analysis)

Week 7: Earth System Modeling: relevant concepts (Model structures, modeling challenges, model validation, data assimilation)

Week 8: Earth System Modeling: applications in different domains (ML-based surrogate models, deep and shallow generators, long-term forecasting)

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