About the Public Health Data Science Concentration
The accurate interpretation and use of data is crucial to understanding health needs and devising and implementing comprehensive, evidence-based solutions. Our Public Health Data Science concentration — one of the first applied data science programs situated within a school of public health — will give you the skills and knowledge to employ cutting-edge data science tools and, in turn, advance effective solutions to pressing public health issues.

What You'll Learn

Data science draws upon multiple disciplines, combining the statistical skills to manipulate data and make inferences, the mathematical skills to model phenomena and make predictions and the computer science skills to manage and analyze large data sets.

Steeped in the public health context, our program offers a unique focus on leveraging the foundational statistical, mathematical and computer science elements of data science to generate useful information from data sources relevant to public health. As a student in this concentration, you will benefit from the instruction and mentorship of top-ranked faculty in the biostatistics department and across the Gillings School. Our chief focus is to optimize data science to help address the most critical public health problems in the world today.

This program will empower you with the knowledge and skills to achieve the following core competencies:

Manage public health data for use in analysis.

appropriate data visualization methods to communicate reproducible research results.

appropriate data analysis and machine learning methods to solve public health problems.

potential sources of bias and uncertainty in public health research.

innovative tools in public health to expand use of appropriately complex statistical methods beyond traditional approaches.

Required Courses & Sample Plan of Study

In addition to the interdisciplinary, 14-credit Gillings MPH Core, students will take six concentration-specific courses on topics such as experimental analysis, machine learning and epidemiology. 

BIOS 512: Data Science Basics

BIOS 645: Principles of Experimental Analysis

BIOS 650: Basic Elements of Probability and Statistical Inference, Part I

BIOS 635: Introduction to Machine Learning

EPID 710: Fundamentals of Epidemiology

BIOS 992: Public Health Data Science MPH Culminating Experience

Fall 2023 Cohort: Public Health Data Science Degree Requirements and Plan of Study (PDF)

Fall 2024 Cohort: Public Health Data Science Degree Requirements and Plan of Study (PDF)

A Note About our MPH and MS

The MPH degree is considered a professional degree with the expectation that most students will pursue employment after graduation. The MS degree is considered a research degree in that students are prepared to pursue a doctoral degree after graduation. Note, however, that there can be exceptions to both.

The MPH in Public Health Data Science at UNC is different from our MS program in Biostatistics in several ways:

The MPH student will take a variety of core public health courses in addition to courses in data science, biostatistics, and epidemiology, plus electives. The electives can be taken across campus with the only requirement that they have a data science component and are eligible for graduate course credit. To date, our MPH students have taken electives in the business, economics, computer science, and informatics departments, for a few examples. In contrast, the MS student will focus primarily on biostatistics courses plus electives in public health. The MS curriculum involves more probability and statistical theory and requires a more rigorous mathematical background. As an example, the MPH curriculum includes a 3-credit hour course in probability and statistical inference in the fall and a 3-credit hour course in experimental design and data analysis in the spring. The parallel requirement for MS students requires 6 credit hours each semester, enabling more topics to be covered, and in more detail.

Note that these comparisons are just for the two programs at UNC. Programs at other universities may differ in their requirements, curricula and career opportunities.


Putting research into action

Scientific discoveries made by Gillings School biostatistician Dr. Michael Kosorok (at left) were put into practice by pediatric pulmonologist Dr. George Retsch-Bogart. The result was better hospital care and better health for children with cystic fibrosis.

Hosted by the Gillings School’s internationally renowned Department of Biostatistics, the Master of Public Health (MPH) concentration in Public Health Data Science is designed for students with a strong mathematical background who wish to develop advanced data science skills — including machine learning, data visualization and statistical inference — and apply them in a public health context.

Your education will equip you with the advanced skills needed to:

  • Manipulate, mine, search and visualize data from large, complex public health data sets (such as disease registries, population data and health care claims data);
  • Apply probability and statistical inference to understand relationships or test hypotheses relevant to health problems and interventions; and
  • Contribute data science leadership and expertise to advance practical solutions to public health challenges.

Data science skills are in high demand among employers across a wide array of sectors. Graduates of this concentration may embark on careers as data scientists, data analysts and statistical analysts, among other options.

Career Opportunities

Our Graduates Work As...
Data Analyst
Data Scientist
Analysis Programmer
Health Informatics Specialist
Research Statistician
Our Graduates Work With...
Government agencies
Pharmaceutical industry
Biotechnology firms
Research institutions

99% of Gillings graduates have a job or continue their education within one year of graduating.

Learn more about the opportunities that await you with an MPH from the Gillings School.

Using data to understand and respond to public health issues
Ready to apply?
Academic Coordinator
Adia Ware
Rosenau Hall 202A

Concentration Leader
Primary Contact: Lisa LaVange, PhD

Featured Events

November 11
All Day
Biostatistics 75th Anniversary Celebration