AI for Earth and Planetary Sciences
E-PSCI 210
Subject & Catalog Number
Course Information
Description
This graduate-level course provides a comprehensive overview of machine learning methods for applications in Earth and Planetary Science (EPS). Topics range from foundational techniques (e.g., regression, clustering, random forests) to advanced deep learning architectures (CNNs, RNNs, GNNs, Transformer, Gen AI, LLM, PINNs, FNO, Agentic AI, Symbolic Regression, XAI). The curriculum integrates methodological lectures with hands-on labs using real-world EPS datasets (e.g., satellite imagery, planetary sensor data). A substantial research project allows students to apply AI workflows to a scientific problem of their choosing, fostering skills in data analysis, model development, and scientific interpretation.
Course Notes
Course is open to advanced undergraduates with instructor permission.
Available for Harvard Cross Registration
