This course introduces students to the fundamentals of data science methods for the design and operation of energy systems. The course is oriented towards students pursuing a technical career in cleantech, or a PhD in the energy sciences and engineering. Course contents include: mathematical modeling & analysis, state estimation, optimization, machine learning, and optimal control. Homework assignments are designed around case studies, including lithium-ion batteries, oil & gas systems, renewable power systems, smart buildings, and electrified transportation. Student teams also execute a self-defined project.

Repeat Rules

Course is not repeatable for credit.