Course materials for Machine Learning for Climate Science and Environmental Sustainability (Columbia Climate School, CLMT5403), Summer 2026, taught by Kara Lamb.
The course introduces the fundamental concepts and methods of machine learning with an emphasis on practical applications to climate science and environmental sustainability — data preprocessing, model selection, evaluation, and the ethical implications of ML in climate research — through hands-on work with real-world datasets.
Built as a Jupyter Book and published to GitHub Pages: https://kdlamb.github.io/ML4Climate2026/