Materials Informatics

By Prof.Sai Gautam Gopalakrishnan | Indian Institute of Science, Bangalore

Learners enrolled: 663 | Exam registration: 129

ABOUT THE COURSE:

With the increasing focus on machine learning and artificial intelligence by industries that operate in the materials domain, and the enhanced digitalization efforts being taken up by several industries, this course will equip students with the necessary machine learning skills that can be applied within the materials domain. The course will not only cover the data science aspects, but also the physics behind materials modelling and computations that generate the datasets used.

INTENDED AUDIENCE: Post graduate and advanced undergraduate students of Metallurgy, Materials Science and Engineering, and Ceramic Engineering disciplines

PREREQUISITES: Students of any metallurgy, materials or related disciplines are welcome.

Summary

Course Status :	Ongoing
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Metallurgy and Material science & Mining Engineering Minor in Metallurgy Minor in Materials Science
Credit Points :	3
Level :	Postgraduate
Start Date :	19 Jan 2026
End Date :	10 Apr 2026
Enrollment Ends :	02 Feb 2026
Exam Registration Ends :	20 Feb 2026
Exam Date :	19 Apr 2026 IST
NCrF Level	4.5 — 8.0

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

Page Visits

Course layout

Week 1: Introduction and terminologies

Week 2: Typical regression and classification workflows

Week 3: Classical models

Week 4: Perceptron and neural networks

Week 5: Convolutions and graph networks

Week 6: Density Functional Theory

Week 7: Molecular Dynamics

Week 8: Statistical Mechanics

Week 9: Lattice models and coarse graining

Week 10: Machine learned interatomic potentials: classical

Week 11: Machine learned interatomic potentials: graphs

Week 12: Advanced topics: transfer learning and generative models

Books and references

• “Computational Materials Science”, June Gunn Lee, Second Edition 2016

• “Understanding molecular simulation: from algorithms to applications”, Daan Frenkel and Berend Smit, Second Edition, 2002

• “Electronic structure: basic theory and practical methods”, Richard M. Martin, Second Edition, 2020

• “Statistical Mechanics”, Donald A. McQuarrie, First Edition, 2000

• “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems”, Aurélien Géron, Third Edition, 2022

Instructor bio

Prof.Sai Gautam Gopalakrishnan

Indian Institute of Science, Bangalore

Prof. Sai Gautam Gopalakrishnan is an Assistant Professor of Materials Engineering at the Indian Institute of Science. His research interests are in using computational and machine learning techniques to advance materials design for energy storage and energy harvesting applications. Sai has a PhD in Materials Science and Engineering from the Massachusetts Institute of Technology and has a dual degree (B.Tech. + M.Tech.) in Metallurgical and Materials Engineering from the Indian Institute of Technology Madras.

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: April 19, 2026 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.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

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 IISc Bangalore .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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