The Public Health & AI Summer School at the 
Mel and Enid Zuckerman College of Public Health (MEZCOPH) 
offers an immersive, hands-on educational experience designed to equip graduate students, research staff, faculty, and public health professionals with essential skills in Artificial Intelligence (AI) and digital public health. Recognizing the critical role AI plays in modernizing public health practice, our summer school fosters deep AI literacy, bridging the gap between public health practitioners and technological innovation.
Participants will explore foundational and advanced topics such as Digital Epidemiology, AI and Machine Learning fundamentals, generative AI applications, digital biomarkers, ethical considerations, and precision public health. Interactive AI Maker Space sessions provide hands-on experience with cutting-edge AI tools, emphasizing practical skills in data management, visualization, spatial epidemiology, and scientific literature organization.
Beyond technical skills, the program emphasizes critical thinking, responsible AI governance, and ethical implications of AI integration in public health. Participants will engage directly with industry leaders and renowned instructors, enhancing their capacity to lead and innovate in an AI-driven landscape.
Financial support through the Dean's Fund is available for students, making the summer school accessible and inclusive. Supported by
 MEZCOPH, the Global Health Institute, and the Data Science Institute
, this initiative positions participants at the forefront of public health innovation, ready to leverage AI for impactful health outcomes globally.
Goals:
Understand the fundamentals of AI and its relevance to public health.
Identify key applications of AI in public health practice, including surveillance, forecasting, risk prediction, and administrative tasks.
Develop essential data analysis and management skills for working with AI, including handling diverse data sources, geospatial data, and visualization and dashboarding tools, working with data platforms and AI assisted analysis methods including low-code and no-code tools.
Recognize and address ethical, legal, and equity considerations in public health AI applications, including data privacy, bias, and transparency.
Learn how to critically evaluate AI tools for reliability and effectiveness.
Enhance communication and teamwork skills necessary for AI-augmented public health work.
Explore practical strategies for implementing AI projects, including piloting and evaluation.
Discuss the importance of human oversight and collaboration in AI systems.
Create your own learning roadmap and build your AI toolbox using free and open source tools alongside commercial products.
The agenda may be subject to changes and updates without prior notice.
Information Source: Global Health Institute | eventbrite

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시간:	Jun 9, 2025(UTC-7) ENDED
주소:	Health Sciences Innovation Building (HSIB)

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