Applied Urban Science and Informatics (MS)

Center for Urban Science and Progress

Program Description

The Applied Urban Science and Informatics MS offered by NYU's Center for Urban Science and Progress (CUSP) provides students with the opportunity to engage in the interdisciplinary study of urban science and informatics and apply technical skills to urban problems. The two-year, 36-credit MS program provides core courses in urban science, urban informatics, and information and communication technology in cities. Students will have the opportunity to select from multiple urban domains and informatics disciplines to gain breadth and depth in the application of big data analytics to urban problems. 

Admissions

Program Requirements

The program requires the completion of 36 credits, comprised of the following:

Course List

Course	Title	Credits
Core Requirements
Lab
CUSP-GX 7000	Data Governance, Ethics and Privacy	0
Urban Data Science Methodologies
CUSP-GX 7013	Introduction to Applied Data Science	3
CUSP-GX 7023	Applied Data Science	3
CUSP-GX 7033	Machine Learning for Cities	3
Urban Science and Policy Methodologies
Select one of the following: 1		3
CUSP-GX 7043	Civic Analytics and Urban Intelligence
CUSP-GX 7053	Innovative City Governance
Capstone Project
CUSP-GX 7103	Capstone Urban Science Intensive I: Project Management	3
CUSP-GX 7113	Capstone Urban Science Intensive II: Data Analysis and Communications	3
Electives
Students may customize their education with specialized CUSP electives in data science, domain applications, and civic analytics. Students take 18 credits of elective offerings in the MS program from the list below, which may be updated from time to time. 1		18
CUSP-GX 5053	Geographic Information Systems
CUSP-GX 8015	Large Scale Data Analysis with Machine Learning I
CUSP-GX 8043	Advanced Spatial Analytics
CUSP-GX 8063	Urban Sensing
CUSP-GX 8073	Big Data Analytics for Public Policy
CUSP-GX 8093	Data Visualization
CUSP-GX 8103	Data-Driven Methods for Policy Evaluation
CUSP-GX 8115	Large Scale Data Analysis with Machine Learning II
CUSP-GX 8123	Disaster Risk Analysis and Urban Systems Resilience
CUSP-GX 900X	Guided Studies
CP-GY 9911	Internship for MS I
CP-GY 9921	Internship for MS II
Total Credits		36

¹

If students take both courses, one will count as an elective.

²

Students may take up to 6 credits of non-CUSP data science or domain application electives from other schools across NYU, including but not limited to the Courant Institute of Mathematical Sciences, Stern School of Business, Wagner School of Public Service, and Tisch School of the Arts. Courses may not, however, be chosen from the School of Professional Studies.

Internships

NYU's Center for Urban Science and Progress (CUSP) offers a distinctive Internship-for-Credit program that enables full-time graduate students to apply their interdisciplinary skills in real-world environments. This supervised program integrates fieldwork with academic learning, allowing students to tackle relevant challenges while gaining valuable industry experience. It is important to note that CUSP does not place students in internships; rather, it is the responsibility of the students to secure an eligible internship and seek adviser approval. Students will complete the internship with comprehensive reports reflecting on their contributions and learnings, deepening their understanding and enhancing their career prospects in relevant industries. This opportunity enriches their academic journey and propels them towards impactful careers in shaping sustainable urban futures.

Capstone Project

During the 6-credit, two-course Capstone Project, students will work in a multidisciplinary environment with a city agency or industry partner to address a current urban challenge in a particular domain, such as transit, public health, or environmental sustainability. Students will play an important role in the project, working with other researchers - and even entrepreneurs - to unlock the potential in big data to make their city better.

Capstone projects may be part of larger, ongoing NYU-CUSP research efforts involving city agencies and NYU‑CUSP industry partners, self-contained projects involving agencies and industry partners, or more entrepreneurial in focus and content, where a team of students will work on developing a new solution derived from their analysis.

Sample Plan of Study

Plan of Study Grid

1st Semester/Term		Credits
CUSP-GX 7000	Data Governance, Ethics and Privacy	0
CUSP-GX 7013	Introduction to Applied Data Science	3
CUSP-GX 7043	Civic Analytics and Urban Intelligence	3
Elective		3
	Credits	9
2nd Semester/Term
CUSP-GX 7023	Applied Data Science	3
CUSP-GX 7033	Machine Learning for Cities	3
Elective		3
	Credits	9
3rd Semester/Term
CUSP-GX 7103	Capstone Urban Science Intensive I: Project Management	3
Elective		3
Elective		3
	Credits	9
4th Semester/Term
CUSP-GX 7113	Capstone Urban Science Intensive II: Data Analysis and Communications	3
Elective		3
Elective		3
	Credits	9
	Total Credits	36

Learning Outcomes

Upon successful completion of the program, graduates will:

1. Identify and analyze urban issues with a focus on communication, innovation and solution building.
2. Develop the technical skills to analyze data and communicate findings.
3. Understand and communicate for decision making at the city and policy making level.
4. Engage, support or contribute to the development of applied research in the service of cities and public good.

Policies

NYU Policies

University-wide policies can be found on the New York University Policy pages.

Tandon Policies

Additional academic policies can be found on the Tandon academic policy page.