Machine Learning for Chemists

This course provides chemists with the tools to apply machine learning in chemical research. It bridges the gap between chemical intuition and computational approaches by teaching how to build, train, and interpret ML models tailored for chemistry. Students will explore case studies ranging from molecular property prediction to catalyst screening and materials design. Practical coding exercises will help participants gain hands-on skills to analyze datasets, implement models, and interpret their results. 

Grading

Exam 50%
Homework 10%
In-class exercise 10%
Project 30%

Syllabus