HLTH 658MMachine Learning Techniques in Health
- Units
- 0.25
- Level
- Graduate
- Faculty
- Health
- Subject
- Public Health Sciences
HLTH 658M as listed in the Winter 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.
Prerequisites
- Must have completed the following:
- HLTH605B - Quantitative Methods and Analysis (0.50)
Antirequisites
None listed.
Leads to
Check it elsewhere for Winter 2026
- Graduate Calendar, Winter 2026The archived entry
- Requirements for Winter 2026Waterloo’s requisite checker
- 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 (shown here)
- Spring 2026 requisites changed
- Fall 2026
- Winter 2024 and earlier in the calendar archives