HLTH 658MMachine Learning Techniques in Health
- Units
- 0.25
- Level
- Graduate
- Faculty
- Health
- Subject
- Public Health Sciences
HLTH 658M as listed in the Fall 2026 Graduate Calendar. The main page has the current version, when it runs, and seats.
This course focuses on the techniques of machine learning (ML) commonly used to solve healthcare and public health problems. Various analytics techniques, including data wrangling, visualization, unsurprised and supervised learning, will be introduced to students. Challenges and strategies related to missing data, imbalanced data and model selections will also be discussed. The learning activities consist of lectures, labs, and a final project to demonstrate the proficiency of ML techniques to solve population health or public health problems. Students who do not have the prerequisites but have completed an equivalent course that provides programming skills may be permitted to enrol in the course at the instructor’s discretion.
Prerequisites
Antirequisites
None listed.
Leads to
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 2025
- Winter 2026
- Spring 2026 requisites changed
- Fall 2026 (shown here)
- Winter 2024 and earlier in the calendar archives