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Jul 31, 2025
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CSCI 4730 - Material Informatics and Data Science
Introduction to data science and machine learning, with case studies in discovery of structure-property relationships and new materials from experimental and computational data. Brief review of required background in linear algebra and statistics with hands-on exercises in Python. Data science topics: model fitting, clustering, dimensionality reduction, ontologies, Bayesian inference, and design of experiments.
Prerequisite: ENGR 2600 ; or equivalent
When Offered: FALL TERM, EVEN YEARS
Cross Listed: MTLE 4730 and MTLE 6730 . Students can only earn credit for one of these courses.
Co-Listed: CSCI 6730
Graded: GRADED
Credit Hours: 3
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