PS 1702 - VISUALIZING AND UNDERSTANDING SOCIAL DATA

Minimum Credits: 3
Maximum Credits: 3
Much of modern data analysis involves presenting and interpreting various forms of ¿social data¿ (e.g. political, economic, and sociological) in a way that is clearly interpretable and understandable to a general audience. This class is a gentle introduction into data analysis and visualization. The key objective is learning through practical examples how messy real world data can be turned into clear and interpretable visualizations, tables, and more. The course will cover topics such as creating maps of spatial data, visualizing trends over time, analyzing text data, merging different datasets and creating reproducible projects. It aims to give students exposure to coding and computer languages that are often used in data analytics in industry, government and academia.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: LG/SNC Elective Basis
Course Attributes: Undergraduate Research

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