Course description

This course addresses pertinent issues relative to planning. Topics vary each semester.

Basic skills in GIS and Python are preferred but not required.

Summer 2024: Ithaca campus

Section ID:CRP 5850 101-SEM
Number:1289
Topic:Introduction to Urban Big Data and Machine Learning
Session:Summer 3-week 1
Class dates:June 3-21, 2024
Final exam/project due:Friday June 21, 9 AM - 12 PM / TBA (see Final exams)
Time / room:M-F 9 AM - 12 PM / Sibley Hall 115
Mode of instruction:In person
Credit:3
Grade:Student option
Instructor:Li, W. (wl563)
Max. enroll:15
Notes:Basic skills in GIS and Python are preferred but not required.
Related:Co-offered with : CRP 3850 101-SEM
Notes:

Urban data science is an emergent practice in urban planning and geography that combines: 1) the set of data analysis tools and methods used to understand a wide array of big data and big spatial data sources and, 2) questions of urban development, structure, complexity, theory, policy, dynamics, and outcomes. These approaches enable more spatiotemporally dynamic and granular analyses of cities and allow researchers new insight into urban dynamics. This course will provide a toolkit to speak through data, code, statistics, and visualization. Using open-source data and computational tools in Python and the Jupyter Notebook environment, we will learn how to design testable research questions, collect and prepare data, apply relevant analytical techniques, and present our process and results in an engaging and informative way. A personal laptop will be required. Undergraduates and graduates at all levels are welcome. Basic statistics is a prerequisite; no prior programming knowledge is required.

To enroll:
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