Applied Urban Science
and Informatics

Online Advanced Certificate

An extraordinary opportunity.

An extraordinary opportunity.

NYU CUSP’s new Online Advanced Certificate can be completed from anywhere in the world, personalized to your busy schedule, and is offered at up to a 75% tuition discount to qualified individuals, to help meet this critical urban moment. Our expert faculty members will serve as your mentors in using data for social good – helping cities around the world become more productive, livable, equitable, and resilient. Using synchronous online coursework with support videos and materials, you will explore how data analytics can help solve challenges faced by growing cities worldwide.

The Online Advanced Certificate is designed for: 

  • Anyone with previous studies or professional experience in Urban Informatics. 
  • Public officials or city employees without a STEM background with a desire to learn how to use data to improve urban policy making or city operations.
  • Working professionals interested in the intersection of data and cities.
  • Researchers or consultants currently working to solve complex urban problems.
  • International students or professionals interested in using data for social good in cities around the world.

Did you miss our prospective student webinar? Watch it here!

Program Highlights

12 Credits (4 Classes)

Choose 4 courses (12 credits) from 6 available classes to customize your plan of study and build competencies in both technical and urban policy domains.

Built for Working Professionals

Apply new skills to your current role or prepare for a career change in the exciting field of Urban Informatics. With our remote format, you have the flexibility to learn around your busy schedule.

Master's Credit Validation

If you decide to pursue CUSP's Master of Science, all credits earned after the successful completion of your Advanced Certificate will count towards your degree.

Fully Remote

Through online synchronous classes and support videos and materials, you can learn from anywhere in the world - while still receiving live instruction and personal attention from our faculty.

Taught by World-Class Faculty

All courses are taught by CUSP's faculty members, including experts in the physical and natural sciences; computer and data science; the social sciences; and engineering.

Tuition Discount

Up to a 75% tuition discount is available to qualified applicants to help meet this critical urban moment.

Use Data and Technology for Social Good

How can rapidly growing cities provide a high quality of life to citizens of every socioeconomic status? How will they effectively and efficiently deliver services, address resource allocation, and increase citizens’ access to green space?

With the Online Advanced Certificate, current and future urban practitioners have the unparalleled opportunity to answer these questions and use technology for social good. At the end of the program, you will be able to:

  • Develop smart data-driven urban policies and innovative solutions to help make cities more efficient and equitable.
  • Operationalize questions on urban challenges as actionable, data-driven analyses, and build robust analyses of these questions using reproducible code.
  • Present and communicate data-driven insights on urban challenges to key stakeholders, including city governments and policy decision makers.
  • Understand the application of data analysis and programming tools to social and behavioral sciences, business operations, and urban sciences.
  • Address the ethical implications of data collection and analysis in urban environments.
  • Apply frameworks by which to assess whether data is addressing or exacerbating urban challenges, such as racial inequity.


Students take 4 courses (12 credits) over two semesters. Students choose their plan of study from the following list of 6 courses according to their interests, technical skill levels, and professional aspirations.

Headshot of Martina Balestra

Course Name: Introduction to Programming for Solving Urban Challenges

Taught By: Martina Balestra, Smart Cities Postdoctoral Associate

A variety of technical skills are needed to build analyses that can help us to solve urban challenges. This course is designed to develop programming skills and to gain familiarity with the techniques, concepts, and models of urban informatics computing. Students will learn to program in python through a series of online tutorials, and will be exposed to the leading thinking on urban challenges through readings and discussion. Weekly lectures will demonstrate how these skills can be used to construct analyses through detailed code reviews. Finally, students will have the opportunity to practice these skills as they build an analysis of an urban challenge using real data.

Students will build a technical foundation to help analyze and solve urban challenges, including:

  • A fundamental understanding of programming languages and data analysis tools, including Python, Pandas, Numpy, and Matplotlib
  • How to load, manipulate, parse, and visualize data
  • How to conduct a descriptive data analysis
  • An introduction to using Jupyter notebook
  • How to operationalize questions
  • 20% synchronous (scheduled class discussions)
  • 80% asynchronous (lectures, homework, and readings)

Students will be evaluated on their performance in their weekly homework assignments, participation in weekly discussion group, and other project work.

Stanislav Sobolevsky

Course Name: Urban Data Science

Taught By: Stanislav Sobolevsky, Associate Professor of Practice

The course targets current and future urban practitioners looking to harness the power of data in urban practice and research. This course builds the practical skillset and tools necessary to address urban analytics problems with urban data. It starts with essential computational skills, statistical analysis, good practices for data curation and coding, and further introduces a machine learning paradigm and a variety of standard supervised and unsupervised learning tools used in urban data science, including regression analysis, clustering, and classification as well as time series analysis. After this class, you should be able to formulate a question relevant to Urban Data Science, locate and curate an appropriate data set, identify and apply analytic approaches to answer the question, obtain the answer and assess it with respect to its certainty level as well as the limitations of the approach and the data. The course will also contain project-oriented practice in urban data analytics, including relevant soft skills – verbal and written articulation of the problem statement, approach, achievements, limitations, and implications.

  • A basic understanding of probability and statistics, as well as basic Python coding skills, including Pandas. 

Students will learn the fundamentals of data science and its application to urban environments, including:

  • Data processing and curation
  • Statistical data analysis
  • Applying supervised and unsupervised machine learning for data analytics
  • Addressing urban analytics problems with urban data
  • 30% synchronous (scheduled class discussions, lectures and practice Q&A, class project discussions and presentations).
  • 70% asynchronous (video lectures and pre-recorded practice notebook introductions).

Students will be evaluated on their performance on practice coding assignments, class project reports and presentations, as well as participation in the class discussion forums.

Headshot of Victòria Alsina Burgués

Course Name: Innovative City Governance

Taught By: Victoria Alsina, CUSP Academic Director & Industry Assistant Professor

This course connects urban governance and innovation trends. Urban governance comprises the various forces, institutions, and movements that guide economic, politic, social and physical development, the distribution of resources, social interactions, and other aspects of daily life in urban areas. Public-sector innovation is indispensable to solve the complex urban challenges we are facing and can bring significant improvements in the services that the government has a responsibility to provide, including those delivered by third parties. This course will help students to become public entrepreneurs that know how to effectively deliver data projects into an urban environment and to transform how we govern the city and the world.

Following a Discovery-Design-Delivery approach, students will learn:

  • The complex nature of cities and their governing institutions.
  • Different strategies to define and solve public problems.
  • How we can promote urban governance innovation.
  • Why following a collaborative governance approach is a must and which are the best tactics to promote effective public-private partnerships and networks.
  • How we can support public engagement at all stages of the policymaking cycle.
    how we can connect artificial and collective intelligence in benefit of the public.
  • Different approaches to measuring organizational performance.
  • Understand how we can produce a global impact from the local level.
  • 30% synchronous (scheduled class discussions, guest lectures, in-class exercisesrole-playing activitiesclass project discussions, and Q&A).
  • 70asynchronous (video lectures, and readings).

Students will be evaluated on their performance in their homework assignments and readings, participation in weekly discussions and lectures, class exercises, and other project work.

Headshot of Paul Torrens

Course Name: Geographic Information Systems

Taught By: Paul Torrens, Professor

This course will provide an accessible introduction to the fundamental concepts and operations that underpin Geographic Information Systems (GIS). At their core, GIS rely on geography as an interface to structured and unstructured data that are stored and managed in what are often complex information systems. The course will introduce students to the central components of GIS as commonly deployed in enterprise software, free and open source code libraries, and experimental systems. The course gives equal treatment to the methodology underlying GIS (particularly in spatial science and computer science), and the software operations that collectively enable GIS functionality and applications (particularly data structures, spatial data access, and geometric operations). Hand-on lab sessions will walk students through the use of GIS methods in popular software, including the Google Maps Javascript Application Programming Interface (API), ESRI ArcGIS (ArcMap and ArcGIS Pro), GeoDa, and GIS libraries in R Studio. The course is intended to prepare students for more advanced coursework at NYU CUSP, particularly Urban Spatial Analytics and Advanced Spatial Analytics.

Students will learn a primer on spatial science concepts for information systems, including:

  • Foundations of spatial data science
  • Understanding of the “front end” of GIS, particularly in cartography and computer mapping
  • Understanding of the “back end” of GIS, particularly in data structures and databases
  • Understanding of core operations in GIS, particularly in manipulation of spatial data and the development of geographical analyses
  • Applications of GIS to problem-solving in real world context
  • Introductory exposure to common GIS software in enterprise applications
  • Introduction to research-oriented topics at the forefront of GIS development
  • Technical writing for spatial data science
  • Technical presentations for spatial data science
  • 10% synchronous (scheduled class discussions).
  • 90% asynchronous (video lectures, readings, and other assignments).

Students will be evaluated on their performance in their homework assignments and readings, participation in weekly discussions and other project work, including written essays and a final project presentation.

Headshot of Neil Kleiman

Course Name: Civic Analytics, Urban Intelligence and Data-Informed Leadership

Taught By: Neil Kleiman, Assistant Professor of Practice

This course provides an overview of city government, operations, and management of information and communication technologies within cities and related policy domains. There will be an emphasis on new approaches to urban governance and data leadership ranging from performance management to innovation delivery units to smarter cities frameworks and public entrepreneurship. Throughout the course we will focus intently on the importance of data and how to collect it; and also how it should be presented from a policy, management, and political perspective to ensure impact. In addition, the role of civic engagement and community participation is explored. Case studies and best practice examples will be used extensively.

Students will gain an overview of city operations and related domains, and will:

  • Understand the overall structure and governance of urban operations
  • Analyze drivers, constraints, and metrics of key urban domains
  • Learn about the roles of data and emerging technologies in cities and opportunities and constraints to employing data analytics
  • Realize the role of citizens in the effective functioning of urban systems
  • Develop the skills to create plans and evaluate the effectiveness of technologies in urban government spaces
  • Appreciate the various leadership techniques needed to advance data policy and reform.
  • Understand and master various ‘translation’ methods to convey complex data ideas to a more general policy audience.
  • Understand recent history of data use within urban and civic contexts.
  • Distinguish between public, private and university sector roles in civic sector data use and application.
  • Ability to assess role of big data in both exacerbating and addressing racial inequity.
  • 20% synchronous (scheduled class times).
  • 80% asynchronous (assignments and readings).

Students will be evaluated on their participation in weekly discussions, and performance on assignments, including a semester-long data innovation project.

NYC Energy & Water Performance Map

Course Name: Data Visualization

Visualization and visual analytics systems help people explore and explain data by allowing the creation of both static and interactive visual representations. A basic premise of visualization is that visual information can be processed at a much higher rate than raw numbers and text. Well-designed visualizations substitute perception for cognition, freeing up limited cognitive/memory resources for higher-level problems. This course aims to provide a broad understanding of the principals and designs behind data visualization. General topics include state-of-the-art techniques in both information visualization and scientific visualization, and the design of interactive/web-based visualization systems. Hands on experience will be provided through popular frameworks such as matplotlib, VTK and D3.js

Students will gain a foundation in the principles and designs behind data visualizations. By the end of the course, students will:

  • Understand the value of visualization
  • Understand the capabilities of different techniques in InfoVis and SciVis
  • Understand the principal of interactive visualization
  • Gain knowledge in building interactive visualization systems
  • Learn how to interactive/web-based visualization systems, matplotlib, VTK and D3.js
  • 20% synchronous (scheduled class discussions).
  • 80% asynchronous (video lectures, readings, and other assignments).

Students will be evaluated on their performance in their homework assignments and readings, participation in weekly discussions and other project work, including written essays and a final project presentation.

Informatics with Impact

Whether you are looking to become an urban scientist or take the next step in your current role, CUSP will prepare you for an exciting and rewarding career in the rapidly growing field of Urban Informatics. City agencies, non-profit organizations, technology companies, consulting firms, and other public and private organizations are increasingly looking for data scientists and analytics experts to unlock the potential of their data. Successful completion of the Online Advanced Certificate will help you:

Advance data-driven skills to propel your career in urban analytics and research, including developing innovative solutions to complex problems and urban policies.

Understand how to collect and analyze large quantities of data in a variety of technical and social domains for use in both the public and private sectors.

Expand your technical skillset to include data manipulation and processing using a variety of tools- such as Python and GIS- for use in non-governmental organizations, government and municipal operations, and business.

Develop skills that directly impact your workplace, including engaging directly with field leaders, creating compelling data visualizations, and developing engaging communication and presentation skills.

Apply Today

New York University charges tuition and registration fees on a per-unit basis.* Up to a 75% tuition discount is available to qualified students. * The Board of Trustees of New York University reserves the right to alter tuition and fees. 

All applicants for the Online Advanced Certificate must demonstrate excellent English language skills in reading, writing, speaking, and comprehension. Please review the English Language Requirement Waiver Form to see if you are eligible to waive this requirement.

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