- Schedule of Classes - June 7, 2023 8:54PM EDT
- Course Catalog - June 7, 2023 7:14PM EDT
Course information provided by the Courses of Study 2022-2023.
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.
When Offered Spring.
Prerequisites/Corequisites Prerequisite: CRP 4080 or CRP 5080 (or similar introductory GIS course). Concurrent enrollment in CRP 5000 - Modular Course: Urban Data Science – Practitioner Talk Series required.
Credits and Grading Basis
3 Credits Graded(Letter grades only)
Class Number & Section Details
- MW Sibley Hall 305
- Jan 23 - May 9, 2023
Instruction Mode: In Person
Permission of instructor required. "Students enrolled in this course must also enroll in the CRP 5000 Modular Course (Urban Data Science – Practitioner Talk Series), which will occur bi-weekly." This course is "Introduction to Urban Data Science". We are still awaiting a title and course description change.
Instructor Consent Required (Add)
Disabled for this roster.