Methods of Data Science 1

Catalog description

Introduces fundamental software tools, software engineering practices, and conceptual frameworks from philosophy of science relevant to data science work across the social and behavioral sciences in both academic and industrial contexts. Topics might include version control, exploratory data analysis, data management, code review, and reproducibility. Course assignments include a mix of individual and group projects using real-world datasets. Instances will assume familiarity with a particular modern interactive scripting language, such as R or Python.