Public Health Data Science (MS)

The MS in Public Health Data Science degree program consists of required courses in Biostatistics, Epidemiology and Computing in addition to at least one elective course chosen to complement one or more of these areas. From the required courses, students will learn the foundations of Data Science, including developing the coding skills to acquire, manage and analyze large, noisy health-related datasets.

Students in the MS in Public Health Data Science will learn to wrangle, scrape, create, and manage large health-related datasets; summarize, visualize, and interpret data; apply statistical methods to draw conclusions from the data; use machine learning to reveal features of large, complex health-related datasets; learn the statistical theory behind common data science methods; and effectively communicate results and findings to a broad audience. This program is designed to be a terminal degree, but for students interested in pursing further education, it can be used to lay the foundation for a PhD in Biostatistics, Statistics, Data Science or Computer Science.