— AI & Machine Learning for Earth & Environmental Sciences

Prerequisites & course information

Course Description: Theory and application of machine learning and artificial intelligence to problems in Earth and Environmental Sciences. Model fitting and regression. Feature extraction and classification from remote sensing observations. Supervised and unsupervised learning. Applications to datasets including earthquakes, streamflow, water quality, geochemistry, and petrology. Learning Activities: Lecture 3 hour(s), Laboratory 2 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL). This course version is effective from, and including: Fall Quarter 2026. Learning Activities: Lecture 3 hour(s), Laboratory 2 hour(s). Grade Mode: Letter. General Education: Science & Engineering (SE); Quantitative Literacy (QL).