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Graduate Education at CUSP

Graduate programs at CUSP offer a unique, interdisciplinary and cutting edge approach that links data science, statistics and analytics, and mathematics with complex urban systems, urban management, and policy. The curriculum addresses the necessary technical skills and critical problem solving frameworks in addition to providing research opportunities and real-world experiences through internships and practicums that enable students to be successful in a wide range of career trajectories. CUSP students understand how to work with data at all stages of the data lifecycle from acquisition to visualization. Furthermore, they gain knowledge about cities by using robust and live data in their class projects, applied research activities, and partnering with companies and NYC agencies addressing existing urban challenges.

Curriculum Structure and Program Length

Students tailor their curriculum experience by building on core courses with different tracks, electives, applied projects intensives, and global immersion offerings.

Core Curriculum

Urban Core

The Urban Science Core provides students with a foundational understanding of the theories of urban form and function, and the application of data-driven approaches to urban challenges. The Urban Core gives students a foundation in the extensive social science literature and research on the study of cities. In addition, it provides an introduction to emerging approaches in developing a “science of cities” that pull in methods and logic from the natural and physical sciences. Courses include City Challenge Week, Computational Urban Policy & Planning, and the Urban Science Intensive sequence.

Informatics Core

The Informatics Core prepares students with computational skills to work with large-scale data, from a variety of sources, to understand and address real-world challenges in the urban context. Students will learn the fundamentals of data science/computer science applications such as databases and data management, data mining, visualization, programming, clustering algorithms, naïve Bayes, model selection and specification, and regression models, and machine learning tools to urban problems and datasets.

Program Tracks

Urban Informatics Track (UI)

This track is for students who are looking for deep training in data science and informatics as applied to cities. The track prepares students with the technical capabilities required for applied data science and “big data” informatics. Course in this track will include courses such as Principles of Urban Informatics, Machine Learning for Cities, Applied Data Science, and Urban Spatial Analytics.

Civic Analytics Track (CA)

This track is for students who are more focused on learning how to utilize analytics and data-driven decision-making techniques to inform urban operations and policy decisions. The goal of the Civic Analytics track is to provide students with the skills and experiences needed to develop and implement data-driven analytics projects within city agencies and other organizations or firms working with cities. Courses include Urban Decision Models, Civic Analytics, Applied Data Science, and Civic Technology Strategy.

  • Learn the skills to be successful in data-driven urban operations, planning, and policy career paths
  • Gain the knowledge to apply data collection methods, new analytical tools, and better operational intelligence that yields actionable insight for city management

Program Length

One Year Full-Time Program

The one-year (twelve month) full-time option is ideal for students looking to immerse themselves in a research- and project-intensive environment and complete their degree in an accelerated timeframe. From August to July, you will be part of a transformative experience by learning from world-class faculty and researchers, building a supportive network that will assist you in your academic and professional career as an urban data scientist around the world. You will experience an academically and technically rigorous curriculum that goes beyond theory by bringing together leading experts who are at the forefront of connecting cities and data using the latest informatics and data science tools and techniques.

Two Year Part-Time for Working Professionals

CUSP also offers a two-year MS program that allows working professionals the opportunity to maintain their employment while attending the graduate program on a part-time basis. The curriculum and elective offerings are the same as for those in the one-year, full-time program. Part-time students take courses in the evenings, many with an applied focus on collaborative projects and technical problem solving, which allows numerous opportunities for networking with peers, faculty, and experts in the industry. CUSP’s robust resources for remote collaboration and research create a flexible option for the busy professionals, and enable them to excel both on the job and in their coursework.

Urban Informatics Full Time MS

Urban Informatics Part Time MS

Civic Analytics Full Time MS

Civic Analytics Part Time MS

Urban Science Intensive (Capstone Project)

The Urban Science Intensive is a two-semester capstone sequence that is the experiential learning focus of the program. At its core, it is team-based work on a real-world urban problem, combining problem identification and evaluation, data collection and analysis, data visualization and communication, and finally, solution formulation and testing. Students work on integrated teams with CUSP Agency and Industry Partners exploring the project’s Social Impact. The outcome of the Intensive involves the integration of multiple technical and urban skill sets from each student’s specialization area in their tracks and electives.

Please click here to see examples of previous CUSP student USI projects.


As a student in CUSP’s graduate programs, you will select electives in two areas – data science and domain applications –from a list of pre-approved courses from CUSP and across NYU, including the Courant Institute of Mathematical Sciences, the Stern School of Business, the Wagner School of Public Service, the Tisch School of the Arts. Example electives include: Big Data Management, Information Visualization, Numerical Methods, Monitoring Cities, Data-Driven Traffic Modeling, Energy Informatics, Urban Operations Research, and Digital Strategy.

Global Immersions and Data Dives

As part of the co-curricular education at CUSP, students have the opportunity to participate in a Winter Week immersion (mid-January) program in one of the leading smart cities around the world. This mini-course targets the global perspective on “urban” skills needed to link data science with the public good. The second global opportunity at CUSP is the Spring Break Data Dive, where students travel to different cities around world to work on actual urban challenges using the analytics skills developed during the program. In the Data Dive, the host city provides their data sets and a specific urban problem; students bring their expertise to answer the questions and solve the problems using informatics techniques.


Click here for NYU CUSP’s graduate education course catalogue.