3.0

credits

Average Course Rating

This course introduces the principles of building energy optimization with a focus on the modeling and control of HVAC systems. The curriculum covers HVAC fundamentals, thermodynamics, and heat transfer, progressing to dynamic systems, control theory, and optimization techniques. Key topics include an introduction to system identification, machine learning, and optimal control applied to energy-efficient building management. The course concludes with hands-on coding assignments focusing on implementation of machine learning and control techniques for optimizing the energy efficiency of buildings using high-fidelity simulation frameworks. The students need to posses prior knowledge in: • Differential calculus • Linear algebra • Optimization