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221.684.79
Transforming Health Systems Research through Artificial Intelligence

Location
Internet
Term
Summer Institute
Department
International Health
Credit(s)
3
Academic Year
2026 - 2027
Instruction Method
Online Synchronous (at least one synch session/week)
Start Date
Monday, June 29, 2026
End Date
Thursday, July 9, 2026
Class Time(s)
No class on July 3rd.
M, Tu, W, Th, 8:00 - 10:50am
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
Yes
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
One Year Only
Next Offered
Only offered in 2026
Prerequisite
No prerequisites for this course.
Enrollment Restriction
This course is not restricted.
Description
Artificial Intelligence (AI) has found extensive applications across academic, industrial, and governmental settings. Are you ready to leverage the power of AI in health systems research? No prior experience with coding is required!
Equips students with a basic understanding of AI, from fundamental machine learning concepts to the latest advancements in large language models and generative AI. Applies AI to various health systems research questions via case studies. Fosters practical familiarity and experience through hands-on sessions. Prepares students to leverage AI in addressing the challenges and opportunities in health systems.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Gain practical knowledge in the principles of AI and distinguish between various models, appreciating their conceptual differences, strengths and limitations, within the context of health systems research
  2. Apply AI for real-world health systems research, considering both practical aspects and ethical implications
  3. Communicate the results from AI to stakeholders and inform policy and practice debates
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
  • 20% Participation
  • 20% Assignments
  • 20% Final Presentation
  • 40% Final Project