MPS, Applied AI for Public Health Data Science
Use artificial intelligence and data science to address today’s most pressing public health challenges
Perfect for...
- Applying AI and machine learning to public health and healthcare
- Analyzing large and complex health datasets
- Using data visualization, clustering, and predictive modeling
- Understanding the ethical, equitable, and responsible use of AI
- Translating data and AI insights into public health practice and policy
- Building practical AI and data science skills for careers in government, healthcare, research, nonprofit organizations, and industry
Career Paths
Graduates will be prepared for careers such as:
- Public Health Data Scientist
- Health Data and Analytics Specialist
- Public Health Informatics Specialist
- AI and Health Research Analyst
- Digital Health and Innovation Specialist
- Public Health AI Program Manager
- AI Policy and Governance Specialist
- Responsible AI and Ethics Lead
- Population Health Analytics Lead
- Public Health Technology and Innovation Lead
- Data and Analytics Consultant
- AI and Health Strategy Consultant
- Director of Public Health Data Science
- Director of Public Health Informatics
- Director of Digital Health and Innovation
- Director of AI Strategy and Implementation
- Director of Population Health Analytics
- Director of Responsible AI and Governance
Program Overview
The Master of Professional Studies in Applied AI for Public Health Data Science is an interdisciplinary professional degree that brings together public health, epidemiology, biostatistics, data science, and artificial intelligence.
Students learn how to work with complex health data, apply modern AI and machine learning approaches, learn how to apply AI for synthesizing vast amounts of health data, and translate computational findings into meaningful public health decisions.
The program emphasizes applied learning and responsible AI, preparing graduates to use emerging technologies while understanding important issues related to bias, ethics, equity, transparency, and strengths and weaknesses of AI applications in public health.
Drawing on expertise across the University of Maryland, the program prepares students for careers at the intersection of AI, data science and public health.
What You Will Learn
Graduates of the program will be prepared to:
- Apply artificial intelligence and machine learning methods to public health data.
- Analyze complex health and population datasets using modern computational approaches.
- Integrate principles of epidemiology and biostatistics into AI-driven analyses.
- Evaluate the accuracy, validity, bias, and limitations of AI systems used in health.
- Apply ethical and responsible AI principles to public health research and practice.
- Communicate AI-generated evidence to public health practitioners, policymakers, and other stakeholders.
- Translate AI and data science findings into practical solutions for real-world public health challenges.
- Lead diverse teams in AI, public health, and public policy.
Program Requirements
Students complete interdisciplinary coursework spanning public health, epidemiology, biostatistics, artificial intelligence, machine learning, and responsible AI.
AT-A-GLANCE PROGRAM FACTS
- 30 CREDITS
- Professional Master's Degree
- Full-Time / Part-Time Options [if applicable]
CORE AREAS OF STUDY
- Public Health Foundations
- Epidemiology
- Biostatistics
- Data Science
- Artificial Intelligence
- Machine Learning
- Responsible and Ethical AI
- Applied Public Health Data Science
- Capstone / Applied Project
Admissions
WHO SHOULD APPLY?
This program is designed for professionals and emerging leaders who want to shape how AI and data are used across public health, health care, policy, and related sectors. Applicants may come from public health, health care, government, policy, technology, data science, research, or other fields and do not need to have a traditional computer science background.
APPLICATION REQUIREMENTS
Applicants should hold a bachelor’s degree from an accredited institution. Application materials include:
- Online graduate application
- Résumé or CV
- Statement of purpose describing professional goals and interest in AI and public health
- Official academic transcripts
- Letters of recommendation
Prior programming or advanced technical experience is not required.
APPLICATION DEADLINE
Priority Deadline: March 30th 2027
Final Deadline: April 30th 2027
PROGRAM START
[June 1st 2027]
Contact Us
Jeremy Rubin , PhD
Assistant Professor
Department of Epidemiology and Biostatistics
jrub@umd.edu