This course provides a rigorous treatment to modern tools in data visualization and analytics. The materials will be organized around two overarching themes: 1) creating professional-looking charts in popular statistical software, and more importantly, 2) processing data and presenting analysis results in an effective and visually appealing manner. The first module of the course will demonstrate how to make charts in Microsoft Excel charts commonly used in business reports (e.g. trend graphs, pie charts, and bar graphs). We will also cover data management and preparation for various data structures and formats, such as importing and exporting data, merging and joining datasets, and reshaping, collapsing or aggregating data for analysis purposes. In the second module, we will dive into more advanced topics in visual analytics mainly using Tableau and R. We will cover how to create more sophisticated visualization tools such as thematic maps and interactive dashboards. Students will have the opportunity to work with various data examples and create their own interactive graphs (e.g. with publicly available financial data or healthcare data). Finally, we will cover how to combine data visualization tools with state-of-the-art data science techniques such as cluster analysis, tree-based methods, and natural language processing.

Lecture Hours: 3.00 Lab Hours: 0Total Hours: 3.00