Material Informatics & Data

MTLE-4730

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.

3 credits

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2024
Material Informatics & Data (3c)
  • Ravishankar Sundararaman
Seats Taken: 9/25
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