The program requires 51-59 credits.
Benchmarks:
Each track requires a discipline-specific statistics course and 2-3 courses introducing students to the discipline. (See tracks below for specific courses).
Core Courses and Capstone:
All students take foundational courses in programming, statistics, mathematics, and data science, as well as upper-level courses in database design, data privacy and security, ethics, data sources and manipulation, data visualization, survey fundamentals, and questionnaire design. Students finish the program by completing a required project-based learning capstone.
Track Courses:
Students also take a set of track courses in a discipline that include upper-level method and theory courses, and a set of restricted electives that will allow students to deepen their knowledge of the discipline and apply data science principles to social science research and practice. Additional tracks will be added over time.
