CH EN 536

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Machine Learning and Dynamic Optimization

Chemical Engineering Ira A. Fulton College of Engineering

Course Description

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.

When Taught

Winter

Min

3

Fixed/Max

3

Fixed

3

Fixed

0

Other Prerequisites

or equivalent to CH EN 436

Recommended

ME 575