Machine Learning and Dynamic Optimization is a graduate level course on the theory and applications of numerical solutions of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include physics-based and empirical modeling, machine learning classification and regression, nonlinear programming, estimation, and advanced control methods such as model predictive control.