EAS 5730
Machine Learning in Earth and Atmospheric Sciences
Machine Learning in Earth and Atmospheric Sciences.
Topics
- Identify the machine learning tools and techniques that are best suited for a given geoscience problem and justify their choice.
- Understand the most significant challenges in preparing geoscience datasets for machine learning and apply that knowledge to create machine-learning ready datasets.
- Train and evaluate basic supervised and unsupervised machine learning algorithms in Python using best practices for geoscience problems.
- Interpret outputs from machine learning algorithms and critically evaluate the limitations and biases of those outputs in their scientific context.
- Discuss and critically evaluate the ethical implications of machine learning solutions.
Official roster learning outcomes
Prerequisites & course information
background equivalent to: MATH 1710; CS1110 or CS 1112 or EAS 2900.
Sources
- Course catalogue ↗2026-2027