Course Details
Demystify the world of generative AI and its emerging applications in public health. This non-technical introduction covers key concepts, terminology, and capabilities of modern AI systems like large language models. Explore practical public health use cases including automated literature reviews, clinical note summarization, and health education content generation. Leave equipped to intelligently discuss AI's potential and limitations in public health contexts.
Explore Retrieval-Augmented Generation (RAG) systems and their applications for making health guidelines and research more accessible. Learn how these AI-powered tools can help public health practitioners quickly extract relevant information from large document collections including policy documents, research papers, and case reports. Build a simple prototype that answers questions using your organization's own health documentation. Examples will include: chat with documents, using AI agents/assistants to help you with data analysis.
Learning Outcomes
Understand key concepts and terminology of large language models
Identify practical AI applications for public health workflows
Build a Retrieval-Augmented Generation (RAG) system prototype
Implement document chat functionality for health guidelines
Evaluate AI limitations and ethical considerations in health contexts
Design AI-assisted workflows for two use cases: knowledge management and/or data analysis
Course Prerequisites
Intro to Python
Topics Covered
AI, Data Visualization