CIVENG 295
Data Science for Energy
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.
Topics
- This course provides an introduction to emerging smart energy systems and the associated fundamental concepts in control systems theory
Official catalogue course objectives and student learning outcomes
Sources
- Course catalogue ↗2026-2027