Data Science Fundamentals for Energy I - Understanding Data

Catalog description

Credit 1.5. 1.5 Lecture Hour. Fundamental concepts and methods applied in data science, focusing on energy applications; topics include probability theory, probability distributions, statistical data modeling and inference, linear regression and predictive models, time series forecasting, dimension reduction, introduction to machine learning, and implementation of algorithms. Prerequisite: Graduate classification; ENGY majors only.