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HLTH 650Applied Machine Learning and Artificial Intelligence in Public Health

Units
0.50
Level
Graduate
Faculty
Health
Subject
Public Health Sciences

Not in the current Graduate Calendar. Shown as it appeared in Spring 2024.

When it runs

  1. F24
  2. W25
  3. S25
  4. F25
  5. W26
  6. S26
  7. F26
  8. W27
  9. S27

Ran in 0 of the last 7 terms. Winter 2027: not on the schedule. Spring 2027: schedule not out yet.

This course introduces machine learning (ML) algorithms that are commonly used in artificial intelligence (AI) in healthcare and public health settings. Students will have hands-on experiences in making linkages across multiple datasets, developing ML algorithms to find patterns, and generating evidence and predictive models that help inform decision-making for policymakers and public health organizations. Challenges related to AI in health data will also be discussed, including data quality, explainability of artificial intelligence, unethical use of AI, and vulnerabilities in datasets that pose a threat to privacy and appropriate use of AI in the public health domain.

Prerequisites

  • Must have completed at least 1 of the following:
    • HLTH605A - Regression Models (0.50)
    • HLTH605B - Quantitative Methods and Analysis (0.50)

Antirequisites

None listed.

Leads to

No course lists it as a requisite.

Check it elsewhere for Fall 2026

Calendar versions

Graduate Calendar

Older Graduate Calendars

In 9 terms, Spring 2021 to Winter 2024