Data-Driven Dynamic Systems

4 credits

Covers techniques for modeling time-dependent systems using data, and discovering interpretable dynamical models using machine learning. Students choose among several other data-driven dynamics topics, including nonlinear system identification tools, operator-theoretic/Koopman methods, and physics-informed deep learning. Recommended: proficiency with writing code in Python. Offered: Sp.