Network Data Science

Catalog description

This course provides an overview of the tools most commonly used to collect, analyze, and visualize network data. For each type of analysis, the underlying theory, assumptions, and mechanics of how each analytical tool works, are discussed, along with appropriate interpretation and visualization of the results. The course is designed for students from any major with real-world examples drawn from the social and behavioral sciences, economics and finance, biology, history, anthropology, social media, public health, and government. Students of all skill levels are welcome, including those with limited or no statistical, mathematical, or programming backgrounds. All analysis skills will be taught in class. However, it is highly recommended, but not required, that students complete DATA 2020 or an equivalent course in statistics and/or data analysis, preferably one that utilized the statistical computing programs R and RStudio, prior to enrollment.