Master of ScienceApplied Urban Science
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.
This 30-credit program is designed to offer students flexibility to design their curriculum to fit their personal and professional interests. Students may seek deep training in data science and informatics as applied to various domains related to cities, or focus more on learning how to utilize analytics and data-driven decision-making techniques to inform urban operations and policy decisions.
With this degree you will:
- Learn the skills to be successful in data-driven urban operations, planning, and policy career path and;
- Gain the knowledge to apply data collection methods, new analytical tools, and better operational intelligence that yields actionable insight for city management.
Program Length and Curriculum Structure
Students tailor their curriculum experience by building on core courses with different tracks, electives, applied projects intensives, and global immersion offerings. Curriculum and course sequencing is subject to change.
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.
Full-time students take 12 credits in the fall and spring semesters, and 6 credits in the summer.
Two Year Part-Time Program
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.
Part-time students take 6 credits in each of their fall and spring semesters, and 3 credits each summer. Part-time students may also choose to take 0 credits in their first summer semester and 6 credits in their final summer semester.
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.
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.
Required Core Classes (18 Credits)
For CUSP course descriptions, please visit our course catalogue here.
- Principles of Urban Informatics
- Civic Analytics & Urban Intelligence
- Applied Data Science
- Urban Spatial Analytics OR Urban Decision Models
- Urban Science Intensive I
- Urban Science Intensive II
Electives (12 Credits)
As a student in CUSP’s graduate programs, you will further customize your education with specialized CUSP electives in data science, domain applications, and civic analytics. Students may also take up to two 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.
To introduce students to the field of Urban Informatics and help prepare students for their graduate students, NYU CUSP requires students to take part in 3 non-credit programs at the beginning of their degree. These courses help students learn the skills necessary for a successful academic career, discover resources at CUSP and NYU, and connect with other students.
Urban Computing Skills Lab (Pre-Fall)
The Urban Computing Skills Lab (UCSL) is a series of online sessions designed to build a common skill set and familiarity with techniques, concepts, and models for urban informatics computing. The labs focus on programming skills in Python and a refresher of statistical methods using built-in and scientific packages for python.
City Challenge Week (Pre-Fall)
City Challenge Week is the start of the MS in Applied Urban Science and Informatics program and CUSP’s new student orientation. The intensive 4-day program includes a number of speakers, workshops, academic boot camps, and events that introduce students to CUSP, the field of urban informatics, and NYU resources.
Data Governance, Ethics & Privacy Lab (Fall)
This supplementary lab teaches students to recognize where and understand why ethical issues can arise when applying analytics to urban problems. Students consider issues across the lifecycle of projects that aim to improve city life through data-driven decision-making, starting with collection and moving through the management, sharing, and analysis of data.
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.
Optional Student Immersions
Global 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.