CHEM 487/542
Chemical Data Science
Chemical Data Science is designed for students and researchers from a broad range of backgrounds. The lectures give a careful explanation of technical details for people who want to understand or develop methods, while the hands-on sessions emphasize practical applications so you can use data science and machine learning in chemistry without needing every derivation on day one.
Concepts, derivations, model assumptions, and technical depth.
Coding, chemical datasets, model training, prediction, and interpretation.
Offered every spring semester.
Lectures and hands-on computational lab sessions.
Supported by NAIRR Classroom, No. NAIRR250481.
Evaluation
Class participation, including attending lectures and hands-on sessions and actively asking questions.
Hands-on assignments with coding and computational tasks, along with analysis of results.
Capstone project summarized as a project report and a 20-minute talk.
Schedule and Course Materials
Lecture notes and lab codes for the first 17 lectures are linked below. More materials will be added for Spring 2027. If you use any part of this content, please acknowledge the source.
Equivariance Neural Networks
Laurence Giordano
Self-Driving Lab and Agentic AI
Self-reading