INFO 5430

Urban Data

Course Description

Course information provided by the 2025-2026 Catalog.

This course provides a broad overview of the opportunities and challenges related to urban data and helps familiarize students with key datasets and the tools and methodologies to visualize and analyze them.The course will introduce a framework to reason about urban data and will present various tools and methodologies to process the data, including data mining, machine learning, GIS, network analysis, simulation, agent-based modeling, and data visualization. Traditional Big Data challenges will be reviewed and the associated challenges speci?c to urban data such as quality, privacy, bias, and data governance will be highlighted. Students will also be introduced to the relevant optimization and simulation models so as to enable them to leverage these tools for data-driven decision-making and creating policy.

Prerequisites REF-FA25/Corequisites REF-FA25 INFO 5410. Corequisites: None.

Enrollment Priority REF-FA25 Enrollment limited to: Cornell Tech students.

Last 4 terms offered (None)

Outcomes REF-FA25

• Discover relevant open data datasets to answer questions related to a given urban data issue.
• Think critically about new kinds of urban data in terms of collection, storage, and processing; students will also be able to assess issues related to privacy and bias.
• Ingest, process and visualize urban data including tabular data, GIS data or graph data.

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