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Course11310892250 lectures

Materials Informatics

Prof. Sai Gautam Gopalakrishnan · IISc Bangalore

Start with lecture 1 At NPTEL

Lectures

Week 1: Introduction to machine learning in matrials science and python coding

  1. Evolution of Materials modelling Video
  2. Introduction to Machine learning Video
  3. Anaconda installation and python basics Video
  4. Functions and classes Video
  5. Numpy basics Video
  6. Pandas basics Video

Week 2: Introduction to Regression and Classification

  1. Regression Video
  2. Regression (continued) Video
  3. Classification Video
  4. Classification (continued) Video
  5. Regression and classification example on materials data Video

Week 3 Classical machine learning models

  1. Regression models Video
  2. Regression models (continued) Video
  3. Classification models Video
  4. Support vector machines and decision trees Video
  5. Ensemble models Video
  6. Ensemble models (continued) and dimentionality reduction Video

Week 4 Perceptron and neural networks

  1. Comparison of classical models on materials data Video
  2. Neural networks Video
  3. Neural networks with keras and tensorflow Video
  4. Neural networks with pytorch Video

Week 5 Convolutions and Graph Networks

  1. Neural networks example on materials data Video
  2. Convolutions Video
  3. Graph Networks Video
  4. Crystal Graph Convolutional Neural Networks Video

Week 6 Density Functional Theory

  1. First Principles methods Video
  2. Density Functional Theory Video
  3. Exchange Correlation Functionals Video
  4. Basis sets and Pesudopotentials Video
  5. DFT hands on Video

Week 7 Molecular Dynamics

  1. Introduction to Molecular Dynamics Video
  2. Molecular Dynamics (Continued) Video

Week 8 Statistical Mechanics

  1. Introduction to Statistical Mechanics Video
  2. Statistical Mechanics - I Video
  3. Statistical Mechanics - II Video

Week 9 Lattice models and coarse graining

  1. Introduction to lattice models Video
  2. Lattice models and Monte Carlo simulations Video
  3. Cluster expasnion hands on Video
  4. Monte Carlo simulation hands on Video

Week 10 Machine learned interatomic potentials

  1. Introduction to machine learned potentials Video
  2. Machine learned interatomic potentials (continued) Video
  3. Atomic cluster expasnion Video
  4. Machine learned interatomic potentials hands on Video

Week 11 Transfer learning

  1. Transfer learning -I Video
  2. Transfer learning -II Video
  3. Transfer Learning hands on Video

Week 12 Generative models

  1. Diffusion Models Video
  2. Diffusion models hands on Video
  3. Large Language Models Video
  4. Large Language Models hands on Video

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IISc Bangalore
Department
Metallurgy and Material Science
Teacher
Prof. Sai Gautam Gopalakrishnan
Level
Undergraduate
Language
English
Subjects
Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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