Explore population-health questions through study design, descriptive analysis, and introductory statistical modeling.
The program introduces the logic of health-data research using an appropriately accessible dataset. Learners move from a research question to variable definitions, cleaning, statistical analysis, and interpretation using R or Stata. Work emphasizes observational-study limitations, ethical data use, and clear communication rather than clinical conclusions.
Proposed learning outcomes for this program example:
The sequence below illustrates how this program’s content can be organized. Topics, pacing, and project depth are adapted for each offering. This is not an archived record of a specific cohort’s weekly syllabus.
Build a research workflow from Python data preparation to machine-learning evaluation and an applied project.
Use systematic review methods and R to synthesize research evidence and interpret quantitative findings.
Compare predictive models and examine how uncertainty changes the interpretation of data-driven decisions.