Master of ScienceApplied Urban Science
Graduate Courses 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.
CUSP-GX 1001: Urban Computing Skills Lab
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.
CUSP-GX 1000: City Challenge Week
City Challenge Week is the start of the MS in Applied Urban Science and Informatics program and CUSP’s new student orientation. The intensive, week-long 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.
Working in teams, students are also challenged to address a significant, persistent urban problem by developing an analytical framework to model and understand the problem, identifying data sources and needs, and presenting a potential analytic solution and implementation strategy. NYU CUSP students share their findings and solutions to the entire cohort at the end of the week.
CUSP-GX 1007: Data Governance, Ethics and Privacy
This class will teach you to recognize where and understand why ethical issues can arise when applying analytics to urban problems. You will 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. You will learn how to parse the unique privacy implications of persistent monitoring of activities in putatively public space, the introduction of sensors and other forms of instrumented measurement into the built environment, the repurposing of government data for uses not anticipated at the time of collection, and the kind of analytic techniques that turn these data into actionable insights. The class will also teach you how to assess whether these result in fairly rendered decisions and how to evaluate the desirability of their consequences (from the perspective of various stakeholders). Finally, the class will force you to consider what ethical obligations you may have to those who figure in your research, as well as those to whom the lessons are later applied. You will learn to think critically about how to plan, execute, and evaluate a project with these concerns in mind, and how to cope with novel challenges for which there are often no easy answers or established solutions. To do so, you will develop fluency in the key technical, ethical, policy, and legal terms and concepts that are relevant to a normative assessment of these novel analytic techniques. You will learn about some of the common approaches and tools for mitigating or managing the ethical concerns that these tend to provoke. And by exposing you to a variety of policy documents, the class will help you understand the current regulatory environment and anticipate future developments.
Required Core Courses
CUSP-GX 5002: Principles of Urban Informatics
This course is the introduction to the core disciplines of data acquisition and management, integration, and analytics. In this course, the student will learn the major concepts, tools, and techniques for what informatics can do for cities. It includes background in data management, visualization, and data science, and also includes material not usually covered in computer science courses, including how to best handle spatial-temporal data, and issues related to citizen science and participatory sensing. It presents software tools, frameworks for problem-solving and model selection parameters using data science in the urban context, including basic modeling and analytical methods; visualization techniques, including geographic information systems; working with large datasets and understanding data sources, including instrumentation, physical sensors, imagery, and mobile sensing platforms; explores issues of data ethics, privacy, etc.; and provides an introduction to citizen science, crowd-sourcing, and participatory sensing.
CUSP-GX 6001: Applied Data Science
This course introduces students to the theory, principles and applications of mathematical and computer modeling of data as applied to cities. It will be based on two unified themes: foundations for predictive analytics and decision-making followed by applications in data science. The 1st half of the course will cover predictive modeling using a wide array of examples, including predictive modeling, an advanced treatment of regression, visualization and graphics, and automated analysis for high dimensional data. The second half will introduce students to applications in data science such as analytics of images and video as well as subjective data processing and analysis.
CUSP-GX 6003: Urban Spatial Analytics
Urban Spatial Analytics focuses on developing spatial analysis skills specifically in urban context, which cuts across various interdisciplinary fields like urban land-use planning, socio-economic development, education, public health, real estate, criminal justice, environmental studies, transportation, and urban demography. This course will equip students with Geographic Information System (GIS) concepts to collect, understand, organize, store, analyze and visualize complex urban geospatial data. Students will learn about combining and overlaying local urban datasets (like MapPLUTO, Taxi/Cab data, Tree Census, Transportation & other datasets) with regional and national datasets like US Census, in order to understand spatial relationships and foster critical thinking in addressing urban issues that informs urban and regional policies. Students will gain hands-on training on geospatial data management, advance analyses (geo-statistics, proximity analysis, site suitability analysis, cluster analysis) , visualization techniques, and applications on solving real world problems, using ESRI’s product – ArcGIS (ArcInfo with advanced extensions) as a primary software, however students will be exposed to other web tools like CartoDB, Google Fusion Tables, and others.
CUSP-GX 7003: Civic Analytics and Urban Intelligence
Cities are increasingly data-rich environments, and data-driven approaches to operations, policy, and planning are beginning to emerge as a way to address global social challenges of sustainability, resilience, social equity, and quality of life. Understanding the various types of urban data and data sources – structured and unstructured, from land use records to social media and video – and how to manage, integrate, and analyze these data are critical skills to improve the functioning of urban systems, more effectively design and evaluate policy intervention, and support evidenced-based urban planning and design. While the marketing rhetoric around Smart Cities is replete with unfulfilled promises, and the persistent use (and misuse) of the term Big Data has generated confusion and distrust around potential applications. Despite this, the reality remains that disruptive shifts in ubiquitous data collection (including mobile devices, GPS, social media, and synoptic video) and the ability to store, manage, and analyze massive datasets require students to have new capabilities that respond to these innovations. This course introduces students to computational approaches to urban challenges through the lens of city operations, public policy, and urban planning. Students are exposed to a range of analytical techniques and methods from the perspective of urban decision-making. Issues of city governance, structure, and history are presented to understand how to identify and assess urban problems, collect and organize appropriate data, utilize suitable analytical approaches, and ultimately produce results that recognize the constraints faced by city agencies and policymakers. This is not an easy task, and requires an understanding of urban social and political dynamics and a significant appreciation of data governance, privacy, and ethics. Specific attention is given to domain areas of energy and building efficiency, transportation, public health and emergency response, waste, water, and social connectivity and resilience, as well as the deployment of urban technology at the neighborhood scale. The role of civic engagement and community participation in the context of open data and citizen science is explored, as well as the evolving relationship between, and influence of, informatics on urban governance. Top-down and bottom-up models of innovative service delivery are discussed and debated in the context of public decision-making. Case studies and best practice examples from U.S. and global cities are used extensively, with a particular focus on New York City.
CUSP-GX 7004: Urban Decision Models
This course provides an introduction to computer-based optimization and simulation models for decision-making for government officials and policy makers. The emphasis is on models that are widely used in diverse functional areas, including every day operations such as waste collection, policing and transportation to policy making on environment/climate change to sheltering the homeless. Applications will include resource allocation, workforce planning, revenue management, asset-liability management (public sector finance models), environmental policy modeling, pension and bonding planning, and political campaign management, among others. The aim of the course is to help students become intelligent consumers of these methods. To this end, the course will cover the basic elements of modeling- how to formulate a model and how to use and interpret the information a model produces. The course will attempt to instill a critical viewpoint towards decision models, recognizing that they are powerful but limited tools.
CUSP-GX 5005: Urban Science Intensive I – City Operations & Applied Informatics
The Urban Science Intensive (USI I) is part of a two-semester capstone sequence that is the experiential learning focus of the program. USI I takes place over 14 weeks in the Spring semester and prepares students for delivering Capstone Projects in the summer. The core of the course 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. This project-based course begins with the Social Impact Project, where students are introduced and immersed in problem definition and project delivery skills. The course also lays the foundation for the Capstone Projects, where students work on integrated teams with Agency and Industry Partners, immersed in the public aspects of the project. * *The Urban Science Intensive I course introduces students to their projects and the Agency and Industry mentors involved and develops team-building; students meet with various officials at the relevant agencies and industry partners, tour relevant projects and facilities, and begin to engage the community; student teams define the problem and craft a strategy to identify solutions, inventory available and needed datasets, and explore possibilities for new instrumentation and citizen engagement to support project objectives. This course involves a combination of lectures, student team project work, in-class group work, site visits, and guest speakers.
CUSP-GX 5006: Urban Science Intensive II – Practicum
Student teams engage in projects through the integration and analysis of data, definition and testing of possible solutions, identification of implementation strategies and constraints, and recommendation of a preferred solution and implementation plan. Student teams are challenged to utilize urban informatics within the real-world constraints of city operations and development, while cognizant of political, policy, and financial considerations and issues of data privacy, validity, and transparency. In so doing, student teams will be tasked with creating innovative and replicable solutions to pressing urban problems. The end product of the Intensive sequence is intended to be the result of the integration of multiple skill sets from each student’s area of specialization in domain, discipline, and entrepreneurial/organizational leadership focus.
CUSP-GX 5003: Machine Learning for Cities
The objective of this course is to familiarize students with modern machine learning techniques and demonstrate how they can be applied to urban data. The course is practice-oriented—concepts and techniques are motivated and illustrated by applications to urban problems and datasets. For that reason it involves a significant programming component, with Python as the primary programming language. Topics include a variety of supervised and unsupervised learning methods, such as support vector machines, neural networks, clustering algorithms, ensemble learning, and advanced regression techniques. Strategies for effective machine learning and discussion of the limitations of ML as well as a variety of supplementary techniques are also considered, including model selection and specification, regularization, dimensionality reduction etc.
CUSP-GX 5004: Civic Technology Strategy
The complexity of the urban context – defined by a rich, interlacing network of infrastructure, systems, and process that cuts across all sectors: public, private, and non-profit – requires that any large and/or innovative technology project take into account the many factors that go into developing a feasible, viable, and desirable project scope, as well as planning and managing against it. This course will be a case-based investigation into frameworks, methods, and tools for developing the strategic perspective in which to scope, plan, and manage technology projects in the urban context. Some the methods and tools we will consider include those drawn from different schools of strategy and management. They include: BOSCARD / Project Charter, Three-Point Estimating, Work Breakdown Structures (WBS), PERT, Critical Path Method, RACI Matrix, RAID Logs, MARCI Charts, Product Backlogs, Sprint Backlogs, User Stories, and Scrum Taskboards.
CUSP-GX 6002: Big Data Management and Analysis
This course will provide an understanding of Big Data and current technologies for managing and processing Big Data. At the course end, students will have the ability to decipher when and which software tools to utilize for a particular project/urban challenge: e.g. NoSQL for web UI, Spark for back-end, SQL for transaction controls, etc. The course is designed to provide a high-level understanding of big data platforms.
CUSP-GX 6004: Advanced Spatial Analytics
Course description coming soon.
CUSP-GX 6005: Data Driven Mobility Modeling
The goal of this course is to provide the students with the tools and methods to understand basics of traffic flow theory, modeling and simulation. The emphasis will be on the use of real-world data to supplement the understanding of the theory behind the models. Small scale simulation models will be developed, tested and validated against real-world data.
CUSP-GX 7005: Science of Cities Seminar
The CUSP Seminar brings together researchers from the CUSP Partners and outside institutions to discuss the latest thinking on urban informatics and smart cities. In this teaching seminar, weekly presentations provide students with the unique opportunity to learn and discuss current research, case studies, and best practices from those directly involved with developing and implementing data-driven solution. The seminar is designed to offer graduate students in the final semester of their degree with a thorough understanding of the current opportunities and challenges they will address following their graduation. It also introduces them to research methods and approaches in the field of urban informatics, allowing them to work individually on a topic of interest in their chosen domain and discipline specializations. The seminar also serves as a networking opportunity for students on the job market and for those interested in pursuing research careers. Specific topics will be selected by the instructor.
CUSP-GX 7006: Entrepreneurship for Urban Technology
Course description coming soon.
CUSP-GX 7007: Monitoring Cities
The world’s urban population is growing by nearly 60 million per year; equivalent to four cities like New York annually. Monitoring the chronological growth of key attributes of cities, as well as quantifying their current conditions presents a great potential for positive change. Through the acquisition of new data, there are immediate opportunities to influence the sustainable growth of small and medium size cities. There is also the potential for alleviating the extremes in Megacities, where conditions have reached a critical and unmanageable state. Looking at cities as interdependent networks of physical, natural and human systems, this course provides a perspective on how to monitor the function and wellness of these systems. Students obtain an understanding of needs assessment, planning, and technical approaches for instrumenting a city. This includes monitoring patterns of activity, mobility, energy, land use, physical and lifeline infrastructure, urban ecology, vegetation, atmosphere and air quality. The expected outcomes of this course is a comprehensive understanding of what can be instrumented and the monitoring architecture for acquiring and generating new data about cities.
CUSP-GX 7008: Operations Research for Cities
This course provides a foundation for understanding the operations of an organization, with particular emphasis on urban government and not-for-profit organizations. The objective is to provide the basic skills necessary to critically analyze an organization’s operating performance and practices and determine if the agency’s operations are properly supporting policy initiatives. Such knowledge is important for careers in a variety of areas, including general management and consulting.
CUSP-GX 7009: Urban Sensing
Remote sensing technologies are becoming increasingly available at better resolution levels and lower costs. This course will provide an overview of some of the most common technologies in the areas of imagery, video, sound, and hyperspectral data that can be facilitated through smart phones or other readily accessible means. Students will be given a formal introduction to the aforementioned four areas and then be afforded an opportunity for hands on training in data collection and data analysis. In the course will have the opportunity to work in small groups to investigate an urban problem of interest to them at a site of their choosing. The teams will use these new learned technologies in tandem with other publicly accessible data (either formally available or also collected by the researchers) to investigate a working hypothesis about their chosen urban problem for their particular site.
CUSP-GX 7010: Urban Informatics for Sustainable Cities
This course is designed to give science, engineering and quantitative social science students from all backgrounds an in-depth overview of the challenges and opportunities that face future cities, ones that need to be met by a convergence of expertise and knowledge from engineering, public policy, social science, and data science. It is designed to be hands-on in the application of data analytics to specific city operational, policy, and planning challenges. Students will work with data from NYC and other cities on a range of sustainability-related problems. The course covers emerging models and systems approaches to the study of cities, the role of data and informatics in city operations and planning, and the application of ICT, IoT, and analytics to urban infrastructure systems. The course introduces cities as multi-dimensional complex adaptive systems whose emergent properties act over many spatio-temporal scales.
CUSP-GX 2599: Science in the City Project
Course description coming soon.
CUSP-GX 8001: Building Efficiency and Performance
This course provides an advanced introduction to building energy efficiency and the role of data in understanding and impacting building performance. The course explores resources for building data and discusses the role of multiple stakeholders affecting energy consumption and efficiency in buildings. Students are introduced to green building rating and certification programs, as well as the potential of performance and prescriptive-based codes to influence building design and patterns of energy use. The growing significance of building instrumentation and controls is presented in the context of new data sources and techniques for building performance optimization. The course engages students to consider behavioral, financial, and policy-driven feedback loops in the potential for global reductions in energy consumption and improvements in efficiency. Finally, students are challenged to view buildings as a system of systems and to analyze energy efficiency at the building, district, portfolio, and city scale.
CUSP-GX 8002: Innovation and Entrepreneurship
Course description coming soon.
CUSP-GX 8003: Energy
Course description coming soon.
CUSP-GX 9001: Independent Study
Students engage in individual research and specific projects in a selected field under the supervision of a member of the faculty and with the permission of the Deputy Director of Academics. Open only to students in the spring and/or summer semester(s). To register for this course, the student must obtain the written approval of his or her faculty adviser. Three (3) credits per semester.
CUSP-GX 9002: Advanced Topics in Urban Informatics
This course is designed to address timely issues in one of the informatics disciplines, broadly grouped into data collection and management, data integration and visualization, and data analytics. The course is a survey of the latest applications of the field of urban informatics, selected based on current projects and research undertaken at the Center for Urban Science and Progress. It combines lectures, guest speakers, and hands-on application of informatics using urban datasets. The course is divided into three components, including data collection and management as it relates to the specialization of the course, discipline-specific skills in areas of big data, and application of the informatics. Students will work directly with actual datasets on current, real-world city problems in various urban domains, as well as applications to theoretical problem sets.