Process Systems Engineering Courses

Process Systems Engineering (PSE) is an interdisciplinary field of process design, operation, and optimization.

The following courses are online resources from beginning to advanced topics. The beginning topics are focused on introductory computing while the more advanced topics are focused on theory and methods for control, optimization, and machine learning.

Introductory Programming

Computer programming is a pre-requisite with available short-courses on Python, Matlab, and Java. The Begin Python, Matlab, and Java courses have 12 modules and can be completed in 2-3 hours each.

There are additional links on the CACHE teaching resources for Computer Programming.

Process Dynamics and Control

Automation is transforming many industries. Process dynamics are how a system changes with time and control is concerned with automatically adjusting actuators to regulate a dynamic process, typically to a set point.

The Process Dynamics and Control courses are 14 week courses that are intended for self-study. There are additional links on the CACHE teaching resource page for process control.

Data Science, Optimization, and Machine Learning

Data science is an inter-disciplinary field that uses algorithms to extract useful information from data. Machine learning is the ability to automatically learn from data without being explicitly programmed. Once a cause-and-effect relationship is learned or programmed, optimization can determine the best result by running many different scenarios to find feasible and optimal outcomes. Dynamic optimization is the application of optimization to time-varying systems.

Seminars and Webinars

There are many opportunities to learn from and interact with experts. In-person seminars and live webinars give an opportunity to engage with the speakers to learn from their disciplines.