Data Science

This course is the foundation for introducing students to key topics in data science, including data acquisition/preparation and exploratory data analysis. Major topics include an introduction to the R programming language and RStudio integrated development environment, working with modern data formats (e.g. XML, CSV, JSON, XLS, XHTML), data import/export (e.g. files, APIs – application programming interfaces – , web sites, databases), finding data to augment analyses, and exploratory data analysis & visualization.

This course is an applied statistics course that introduces students to key topics in data science, including exploration, statistical data analysis and communicating the results of data analyses. Major topics include advanced R programming language concepts, working as a standalone data analyst and within a team, organizing analysis projects, modeling with univariate, bivariate and multivariate data and basic clustering, classification and time series analysis and forecasting.