CHE 626Applications of Machine Learning
- Units
- 0.50
- Level
- Graduate
- Faculty
- Engineering
- Subject
- Chemical Engineering
When it runs
- F24
- W25
- S25
- F25
- W26
- S26
- F26
- W27
- S27
Ran in 0 of the last 7 terms. Winter 2027: not on the schedule. Spring 2027: schedule not out yet.
This course provides an overview of the core theory and implementation of cutting-edge applications of machine learning in chemical engineering including methods in deep learning (e.g., convolutional neural networks), Bayesian optimization, and reinforcement learning. Application areas are based on traditional and emerging industrial practice which include (but are not limited to) process control, process design, process scheduling, material discovery, process monitoring, and fault detection.
Prerequisites
- Must have completed the following:
Antirequisites
None listed.
Leads to
No course lists it as a requisite.
Check it elsewhere for Fall 2026
- Graduate Calendar, Fall 2026The official entry
- Requirements for Fall 2026Waterloo’s requisite checker
- Schedule of Classes, Fall 2026Instructors, rooms, live seats
- Quest Class SearchWhere you enrol
- Course outlinesSyllabi from past terms (UW login)
- UW FlowStudent ratings and reviews
- WClassesPast sections back to 2004, and who taught them
Calendar versions
Graduate Calendar
- Fall 2026 (shown here)
- Winter 2024 and earlier in the calendar archives