Data Science I: Foundations

3 Credits · Level: Graduate, Juris Doctor

This first course in the core data science sequence teaches Data Science for Public Policy (DSPP) students how to synthesize disparate, possibly unstructured data in order to draw meaningful insights. Topics covered include the fundamentals of object-oriented programming in Python; literate programming; an introduction to algorithms and data types; data wrangling, visualization, and extraction; and an introduction to machine learning methods. In addition, students will be exposed to Git and Github for version control and reproducible research. The objective of the course is to teach students how to incorporate data into their decision-making and analysis. No prior programming experience is assumed or required.