Syllabus

The following are tentative topics that will be covered in the course. The topics may change depending on the pace of the course.

Module 1: Machine Learning

1. Programming in Python

2. Numpy and JAX

3. Regression and Classification

4. Neural Networks

5. Probabilistic Generative Models

6. Normalizing Flows

7. Diffusion Models

Module 2: Machine Learning \(\cap\) Biophysics

1. Multiple Sequence Alignment

2. Directed Coupling Analysis

3. Protein Structure Prediction

4. Protein Design

Module 3: Molecular Dynamics

1. Boltzmann Distribution and Langevin Dynamics

2. Molecular Dynamics Simulation

3. OpenMM

4. Umbrella Sampling

5. Temperature Replica Exchange Molecular Dynamics

Module 4: Molecular Dynamics \(\cap\) Biophysics

1. Protein Folding

2. Free Energy Calculation

3. Protein-Ligand Binding

4. Computational Drug Design