Artificial Intelligence in Action: Course Offerings

AI in Public Health: Opportunities, Applications, and Concerns
This course provides an in-depth exploration of AI technologies and their relevance to health and public health-related fields. Students will learn how AI systems work, explore different AI approaches, and examine the critical role of data in driving AI solutions. The course will also address potential biases and ethical challenges in AI, equipping students to critically analyze and mitigate risks. Through case studies and practical applications, students will gain insights into how AI can support informed decision-making in health and public health contexts.

Digital Tech and Health Across the Lifespan
This course provides an in-depth exploration of AI technologies and their relevance to health and public health-related fields. Students will learn how AI systems work, explore different AI approaches, and examine the critical role of data in driving AI solutions. The course will also address potential biases and ethical challenges in AI, equipping students to critically analyze and mitigate risks. Through case studies and practical applications, students will gain insights into how AI can support informed decision-making in health and public health contexts.

Expanding A Course on The Use of AI in Health and Public Health
In the Spring of 2025, the Center for Advanced Technology and Communications in Health (CATCH) launched the first ever Introduction to AI course at CUNY SPH. Students indicated that they enjoyed the course and found it very helpful, which motivated Dr. Lee to apply for AI Innovation funding to further augment the course and create an asynchronous version to increase its reach. He also wanted to lay the groundwork for other versions of the course, such as ones that can be taught in shorter time frames for busy professionals.
This course is funded with the help of a $25,000 grant from AI Innovation Fund

Responsibly bringing agentic AI into the classroom
Using AI tools to automate repetitive workflows is becoming standard practice in industry; however, students performing computational work struggle to identify which tasks can be effectively or responsibly automated. Dr. Rochman and colleagues are developing two courses: a 3-credit elective, “Agentic Systems for Health Analytics,” and a self-paced online module, “AI Governance, Data Sovereignty, and Regulatory Compliance.” Agentic Systems for Health Analytics will provide students an opportunity for supervised, hands-on construction of agentic AI workflows enabling them to perform work that would be impractical without task automation. These agents will be maintained by CUNY SPH within an AI Agent Library emulating enterprise AI deployment. Over time, this library will serve to build AI capacity across CUNY as well as provide students with visible, publicly accessible portfolio projects.
This course is funded with the help of a $25,000 grant from AI Innovation Fund

Informatics and AI Applications in Public Health Nutrition (in development)
Using AI tools to automate repetitive workflows is becoming standard practice in industry; however, students performing computational work struggle to identify which tasks can be effectively or responsibly automated. Dr. Rochman and colleagues are developing two courses: a 3-credit elective, “Agentic Systems for Health Analytics,” and a self-paced online module, “AI Governance, Data Sovereignty, and Regulatory Compliance.” Agentic Systems for Health Analytics will provide students an opportunity for supervised, hands-on construction of agentic AI workflows enabling them to perform work that would be impractical without task automation. These agents will be maintained by CUNY SPH within an AI Agent Library emulating enterprise AI deployment. Over time, this library will serve to build AI capacity across CUNY as well as provide students with visible, publicly accessible portfolio projects.Nutrition Informatics is the practice of taking systematically acquired data and applying it to nutrition questions to create applicable knowledge. This new course will explore the value of cross-pollination of the principals of informatics methodology into applications for public health nutrition. It will examine the use of data from a variety of sources to identify trends to guide planning and intervention. Applicable uses of artificial intelligence in these practices will be discussed and critically evaluated.
This course is funded with the help of a $25,000 grant from AI Innovation Fund