CRP 5680

Introduction to Urban Data Science: Data, Interpretation, and Presentation

Course Description

Course information provided by the Courses of Study 2024-2025.

This course will cover tools for more spatiotemporally dynamic and granular analyses of cities through data, code, statistics, and visualization. Using open-source data and computational tools based in Python and the Jupyter Notebook environment, topics may include data cleaning, linking, and management, open data portals and APIs, exploratory and descriptive spatial data analysis, visualization, both unsupervised clustering and regionalization techniques using machine learning, and supervised techniques such as regression, classification, and model selection. Students will also learn how to design testable research questions, apply relevant data and analytical techniques, present our process and results in an engaging and informative way, and identify the limitations of quantitative analysis. A personal laptop will be required. A lab led by the TA will accompany this course.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: CRP 4080 or CRP 5080 (or similar introductory GIS course).

Satisfies Requirement Satisfies additional methods requirement for M.R.P. students.

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