This course equips students with the skills and tools necessary to address applied data science problems with a specific emphasis on urban data. Building on top of the Principles of Urban Informatics (prerequisite for the class) it further introduces a wide variety of more advanced analytic techniques used in urban data science, including advanced regression analysis, time-series analysis, Bayesian inference, foundations of deep learning and network science. The course will also contain a team data analytics project practice. After this class the students should be able to formulate a question relevant to urban data science, find and curate an appropriate data set, identify and apply analytic approaches to answer the question, obtain the answer and interpret it with respect to its certainty level as well as the limitations of the approach and the data.

Ctr for Urban Sci and Progress (Graduate)
3 credits – 15 Weeks

Sections (Spring 2023)

CUSP-GX 6001-000 (7539)
01/23/2023 – 05/08/2023 Thu
2:00 PM – 4:00 PM (Early afternoon)
at Brooklyn Campus
Instructed by Sobolevsky, Stanislav

CUSP-GX 6001-000 (7540)
01/23/2023 – 05/08/2023 Thu
5:00 PM – 7:00 PM (Late afternoon)
at Brooklyn Campus
Instructed by Sobolevsky, Stanislav