Applied AI in Public Health Practice
Issued by
University of Arizona
Applied AI in Public Health recognizes competency in applying AI to public health through data analysis, geospatial methods, and AI prototyping. Participants demonstrate skills in integrating diverse datasets, creating reproducible workflows, prompt engineering, and evaluating ethical, equity, and bias considerations. Emphasizes real-world problem-solving, interdisciplinary collaboration, and designing AI adoption strategies for health systems.
- Type Validation
- Level Foundational
- Time Hours
- Cost Free
Skills
Earning Criteria
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Participants complete all program requirements, including a pre-assessment to establish baseline knowledge, 32-hours in-class learning, 4- 3-hour hands-on practical activities in AI Makerspace, an interactive check-in during AI Makerspace to demonstrate applied skills, and a post-assessment confirming mastery of concepts and tools. Completion reflects active engagement, skill application, and competency in AI for public health contexts.