ML4Science Winter School

 About the Winter School

This is a week long intensive workshop on Artificial Intelligence/ Machine Learning (AI/ ML) for (Bio)Molecules and Materials, featuring 60 hours of in-person engagement

• 20 hours of classroom style lectures on ML concepts

• 40 hours of hands-on tutorials and mini-project

• 25+ Code repositories

• Focus on practical applications along with exposure to ML concepts

• Equivalent to a 3-credit 500-level course

Who should attend?

This course is suitable for Ph.D. students, early-career researchers working/interested in applying artificial intelligence/ machine learning/ deep learning methods to chemistry and biology. 

Working knowledge of python desirable, but not mandatory.

Lectures (20 hours):

• Basics of Machine Learning

• Artificial Neural Networks:

  • • Feedforward NN

    • CNN

    • RNN

• Feature Engineering and Representation Learning for Molecules

• Graph Neural Networks

• Unsupervised Learning

• Reinforcement Learning (RL) and Direct Preference Optimization (DPO)

• Generative AI:

  • • Variational Autoencoder (VAE)

    • Language Models

    • Diffusion Models

Practicals and Guided Mini-Project (40 hours):

• 25 Code Repositories

  • • Regression Tasks

    • Classification Tasks

    • Generative AI Tasks

    • Optimization (RL) Tasks