Public Health Data Science
Data science is an emerging and dynamic discipline that draws strength from many domains. Although the definition of this field is still evolving, hallmarks of data science include: the principled visualization and analysis of data; the recognition of research reproducibility and replicability; the need to communicate and disseminate results effectively; and an emphasis on substantive collaborative engagement in interdisciplinary research.
The Public Health Data Science (PHDS) track retains the core training in biostatistical theory, methods, and applications, but adds a distinct emphasis on modern approaches to statistical learning, reproducible and transparent code, and data management. The length of the 36-credit program varies with the background, training, and experience of individual students. Most complete the program within two years (four semesters) and begin their studies in the fall semester.
In addition to fulfilling their course work, all PHDS students complete a one-term practicum and capstone experience. The practicum experience is an important element of the PHDS training, as it provides students with the opportunity to apply knowledge learned in the classroom to real-world situations and offers a taste of future career opportunities.
Applicants should have some background in college mathematics, including at least a year of calculus. A semester of linear/matrix algebra is highly encouraged. Students with strong scores on the quantitative section of the GRE are given first preference. As with all Biostatistics programs, the most important ingredients for the MS/PHDS are a facility for quantitative reasoning and a true enjoyment of working with data.
Search the Columbia Directory to find current students in the program.
View competencies, course requirements, sample schedules, and more in our Academics section.