Machine Learning for Earth System Sciences

By Prof. Adway Mitra   |   IIT Kharagpur
Learners enrolled: 2768
This course will start with a gentle recapitulation 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.

INTENDED AUDIENCE: Final year undergraduate, Postgraduate and research students

PREREQUISITES: Machine Learning (mandatory), Deep Learning (optional), a working idea of one or two domains in earth system sciences
Course Status : Completed
Course Type : Elective
Duration : 8 weeks
Category :
  • Computer Science and Engineering
Credit Points : 2
Level : Undergraduate/Postgraduate
Start Date : 25 Jul 2022
End Date : 16 Sep 2022
Enrollment Ends : 08 Aug 2022
Exam Date : 25 Sep 2022 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

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)

Books and references

  1. Handbook of Spatial Statistics, Edited By Alan E. Gelfand, Peter Diggle, Peter Guttorp, Montserrat Fuentes, CRC Press, 2010
  2. Deep Learning for the Earth Sciences, Edited by Gustau Camps-Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein

Instructor bio

Prof. Adway Mitra

IIT Kharagpur
Prof. Adway Mitra is an assistant professor at the Centre of Excellence in AI. He 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.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: 25 September 2022 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.


Average assignment score = 25% of average of best 6 assignments out of the total 8 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team

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