Applied Urban Science
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.
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:
Students take 4 courses (12 credits) over two semesters. Course formats include synchronous and asynchronous learning.
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
Students will be evaluated on their performance in their weekly homework assignments, participation in weekly discussion group, and other project work.
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
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.
Geographic Information Systems
Taught By: Paul Torrens, Professor
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
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.
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.
Students will be evaluated on their participation in weekly discussions, and performance on assignments, including a semester-long data innovation project.
I invite you to join us on NYU CUSP’s historic mission. Data alone will not solve society’s most pressing problems; we need students like you to ensure technology is used responsibly to drive positive change for all.
To be eligible for consideration to the CUSP Online Advanced Certificate, you must submit the following. For more details on each aspect of your application please refer to NYU Tandon’s application requirements.
- Online Application Form
- Application Fee
- Personal Statement
- Official Transcripts and Degree Conferral
- GRE Scores (optional)
- 2 Letters of Recommendation
- Supplemental Questions
- English Language Proficiency Testing (if applicable)
- 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.
Priority Deadline: Applications submitted before December 1st will receive a 75% tuition discount if accepted.
Final Deadline: Applications submitted before August 12th will receive a 50% tuition discount if accepted.
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:
New York University charges tuition and registration fees on a per-unit basis. Use the tuition look-up tool to find out what your tuition and fees will cost. Use the The Board of Trustees of New York University reserves the right to alter tuition and fees.
Join us in our historic mission to make cities around the world better places to live and work.