MSE 504 - Introduction to Machine Learning for Materials Science

Designed to provide the fundamental background of ML methods as applied to practical problems of materials discovery, characterization, and optimization. Covers the basics of the classification, regression, and dimensionality reduction methods, combined physics- and ML based workflows, and introduces the concepts of active learning, experimental planning, and causal learning as necessary elements of decision making. The emphasis is made on low-code hands-on practice. Graduate students will be expected to complete a capstone project by applying machine learning to an aspect of their graduate research or model system.