STAT 209 - Data Computing and Visualization

FC NSMA QFR

4 credits
An introduction to the principles and practice of creating informative and effective data visualizations to summarize and describe patterns in potentially large and complex datasets. In the service of effective and reproducible visualization, principles and tools for automating data manipulation (for example, scraping data from the web, merging data from multiple sources, and cleaning, filtering, and transforming data) will also be covered. Selected topics from machine learning, such as dimensionality reduction and clustering, approached from an applied perspective, may be included in this latter category.