Introduction to Data Science

3 credits · Undergraduate

Provides students with both theoretical and practical knowledge of data science, including accessing data, analyzing data, and presenting data analysis. Data access topics include web scraping, using application programming interfaces and database queries. Data analysis topics include linear regression, logistic regression, and basics of unsupervised machine learning. Data analysis will also cover cross validation. Data presentation topics include univariate and bivariate graphs, lattice graphing, mapping and interactive graphics. Emphasizes literate programming as basis for access, analysis and presentation. Prerequisite: Introductory Statistics or permission of instructor. [3]