Introduction to Health Data Science

Graduate / Professional

Data science offers powerful tools for addressing complex questions in public health and healthcare—from determining optimal social distancing guidelines during a pandemic to understanding treatment effects in observational studies. This course provides a comprehensive introduction to core concepts and recent advancements in data science, with a particular focus on practical applications in these domains. Students learn to translate real-world problems into precise mathematical questions, apply appropriate analytical tools, and effectively communicate findings to diverse audiences. The course integrates three pedagogical components: (1) lectures introducing fundamental concepts and methods, (2) case studies and discussions grounded in public health applications, and (3) hands-on assignments involving reading, programming, and problem-solving exercises, with Python as the primary programming language. Serving as a “trailer” of modern data science tools and techniques, the course equips students to decompose real-world problems into addressable sub-questions, identify appropriate analytical approaches, and navigate the methods literature for more advanced techniques as needed. TTh 3pm-4:20pm