ENMA637

Machine Learning for Materials Science

Prerequisite: MATH461. Recommended: Python knowledge. Restriction: Permission of ENGR-Materials Science & Engineering department. Jointly offered with: ENMA437. Credit only granted for: ENMA437, ENMA489L, or ENMA637. Familiarizes students with basic as well as state of the art knowledge of machine learning and its applications to materials science and engineering. Covers the range of machine learning topics with applications including feature identification and extraction, determining predictive descriptors, uncertainty analysis, and identifying the most informative experiment to perform next. One focus of the class is to build the skills necessary for developing an autonomous materials research system, where machine learning controls experiment design, execution, and analysis in a closed-loop.

Fall 2024

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Fall 2023

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Past Semesters

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* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.