340.631.01
Practical Skills in Using Generative Artificial Intelligence (GenAI) in Public Health
Location
East Baltimore
Term
4th Term
Department
Epidemiology
Credit(s)
2
Academic Year
2025 - 2026
Instruction Method
In-person
Friday, 9:00am - 12:00pm
Auditors Allowed
No
Available to Undergraduate
Yes
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
550.610.81 or 340.611.89 or 340.621.81
Enrollment Restriction
This course is not restricted.
Are you looking to gain practical skills in using generative AI for public health? This course will provide hands-on experience in using GenAI for practical applications, including drafting policy briefs, writing statistical code, developing grant proposals, drafting presentations, and much more!
Provides hands-on instruction to develop practical skills in use of generative AI for public health applications. Uses worked examples and group exercises to build skills in: (a) drafting policy briefs, op-eds and persuasive prose; (b) writing statistical code; (c) data visualization; (d) developing career materials; (e) drafting grant proposals, research products, and teaching materials; (f) summarizing data for decision-makers; and (g) writing more effective interpersonal communications.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Draft a policy memo and op-ed using generative AI
- Write and revise code for statistical analysis using generative AI
- Generate tables, figures and infographics using generative AI
- Draft and revise a resume and cover letter using generative AI
- Draft and revise grant proposals, research products, and teaching materials using generative AI
- Use deep research to summarize data for decision-makers
- Use generative AI to improve the effectiveness of interpersonal communications
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
- 50% In-class Exercises
- 50% Reflection
This course will be taught during a 3-hour session, but we only anticipate 3 hours per week of independent out-of-class work to accompany (since much of the work will be done in-class), for a total of 6 hours of expected work per week. Therefore, even though there will be 3 hours of seat time, the course will only provide 2 academic credit hours.