Urban Analytics, M.S. and Certificate

Build analytical and computational skills to understand complex urban systems through data, GIS, spatial analysis, visualization, machine learning, and AI. Apply these methods to real-world challenges in transportation, land use, housing, infrastructure, the environment, and urban development.

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30

M.S. Credits

15

Certificate Credits

AI

Machine learning + urban analytics

GIS

Spatial analysis + geospatial methods

Explore two interdisciplinary pathways that connect urban planning with GIS, data science, machine learning, and artificial intelligence.

What is Urban Analytics?

Urban analytics incorporates data, spatial analysis, computing, visualization, and artificial intelligence to understand how cities function and to support better urban decision-making.

Study Complex Urban Systems

Use data to investigate patterns in mobility, land use, infrastructure, communities, and the built environment.

Build Technical Skills

Apply GIS, programming, data science, visualization, and machine learning to urban questions.

Support Urban Decisions

Translate analysis into evidence that can inform planning, policy, design, and public or private-sector decisions.

Why UF?

Urban planning expertise meets technical AI training.

Technical AI Coursework

Build AI and machine learning skills through technical courses in engineering, computing, and related fields.

Urban Context is Central

Address real urban challenges through planning coursework and a research project, with pathways tailored to your background.

Cross-department Learning

Learn from faculty across planning, engineering, computer science, and architecture.

Career Pathways

Urban analytics skills can support work in public agencies, consulting, planning and design firms, transportation, environmental planning, and data-focused roles.

Career Areas

  • Urban Data & Analytics
  • GIS & Geospatial Analysis
  • Transportation & Mobility
  • Planning & Policy Analytics
  • Smart Cities & Urban Technology
  • Data Science & AI

Job Titles

  • Data Analyst
  • City Planner
  • Urban Designer
  • Consultant
  • Transportation Planner / Engineer
  • Environmental Planner

Choose the Program That Fits Your Goals

UF currently offers both a full master’s degree and a graduate certificate in Urban Analytics.

M.S. in Urban Analytics

30 credits
12-18 months
Master Research Project

Designed to prepare students to use data, GIS, computing, visualization, and artificial intelligence to understand and address complex urban challenges.

Graduate Certificate in Urban Analytics

15 credits
Option A / Option B
Up to 3 years

Designed for students across disciplines who want to strengthen their skills in urban data analysis, GIS, data science, and artificial intelligence.

What You’ll Learn

Build a balanced skill set that connects urban systems knowledge with spatial analysis, programming, visualization, and machine learning.

Urban Data & Analytics

Work with complex urban datasets and develop analytical approaches for interpreting patterns and change.

GIS & Spatial Analysis

Analyze, model, and visualize geographic patterns using geospatial methods and tools.

AI & Machine Learning

Apply machine learning and related computational methods to urban data and urban systems.

Urban Applications

Connect technical analysis with planning, transportation, land use, policy, and other urban applications.

Curriculum

Review the program structure here, then open the detailed course pages for course titles, credits, terms, policies, and model semester plans.

M.S. in Urban Analytics – 30 Credits

ComponentCreditsOverview
Required Core Courses18Urban data structures, planning foundations, introductory and intermediate urban analytics, and a 6-credit Master Research Project.
Elective Group 1: Urban and Regional Planning6 or 9Planning information systems, geospatial modeling, spatial analysis, transportation and land use modeling, and related urban methods.
Elective Group 2: Machine Learning6 or 9Machine learning, pattern recognition, intelligent systems, and related technical coursework across UF departments.
Total30The elective allocation depends on academic background and applicable waivers.

Graduate Certificate – 15 Credits

Option A

Planning-related Background

9 credits of required core courses, plus 3 credits in Urban and Regional Planning Theory and Methods and 3 credits in Data and Computer Science.

Option B

Computing / Engineering-related Background

6 credits of required core courses, plus 9 credits in Urban and Regional Planning Theory and Methods.

Admissions & Application

Review deadlines and expand the application requirements for the M.S. or Graduate Certificate.

MASTER OF SCIENCE

M.S. in Urban Analytics

Priority Application Deadlines

Fall admissionJanuary 15
Spring admissionAugust 15

Applications submitted after the priority deadline may be considered on a case-by-case basis, subject to program policy.

Applicants complete UF’s Graduate Admissions online application and submit the required materials through the application system.

  • Transcripts showing a 3.0+ GPA.
  • Resume or CV.
  • Personal Statement, 500 words maximum. Address your personal background, life experiences, opportunities and challenges, leadership skills, and values.
  • Statement of Intent, 1,500 words maximum. Explain your interest in urban analytics, how UF’s MSUA program supports your professional goals, your plan of study, and your expectations after graduation.
  • Three letters of recommendation. At least two should be academic letters if you graduated within the last three years.
  • English proficiency through TOEFL or IELTS for applicants whose first language is not English, as required by UF policy.
  • GRE is not required.

The program’s application material notes that admission decisions are typically communicated within about two months of the application deadline.

Questions about your application?

Prof. Zhong-Ren Peng

zpeng@ufl.edu · (352) 294-1491

Apply Now

Graduate Certificate

Graduate Certificate in Urban Analytics

Priority Application Deadlines

Fall admissionMarch 1
Spring admissionNovember 1

Applications are accepted on a rolling basis throughout the year.

  • An accredited bachelor’s degree.
  • Transcripts showing a 3.0+ GPA.
  • Resume or CV.
  • English proficiency through TOEFL or IELTS for applicants whose first language is not English, as required by UF policy.
  • GRE is not required.

Questions about your application?

Prof. Emre Tepe

emretepe@ufl.edu · (352) 294-1487

Apply Now

Faculty & Research

Explore the Urban and Regional Planning faculty profiles below. The Electrical and Computer Engineering row currently shows a profile template; faculty details will be added once participation is confirmed.

Department of Urban and Regional Planning

Peng headshot

Zhong-Ren Peng

Professor; Director, International Center for Adaptation Planning and Design

Email: zpeng@ufl.edu

Urban Planning AI, transportation and land use, information technology for planning, climate adaptation, GIS, and sustainable urban systems.

Research Web
Google Scholar
A man with dark hair pulled back is smiling slightly, wearing a white collared shirt. The background is blurred with hints of green and yellow, suggesting an outdoor setting.

Emre Tepe

Associate Professor

Email: emretepe@ufl.edu

Urban analytics, spatial econometrics, land use change, spatiotemporal modeling, machine learning, artificial intelligence, and big data.

Research Web
Google Scholar
A young man with short black hair, wearing a black suit, white shirt, and maroon tie, smiles in front of a plain white background.

Shenhao Wang

Assistant Professor; Director, Urban AI Laboratory

Email: shenhaowang@ufl.edu

Urban science, deep learning, choice modeling, urban mobility, network analysis, computational urban justice, and generative AI for planning.

Research Web
Google Scholar
Peng headshot

Yan Wang

Associate Professor; Founder and Director, Urban Agility and Resilience Lab

Email: yanw@ufl.edu

Urban resilience, urban analytics, responsible AI, crisis informatics, spatial and infrastructure planning, and smart and connected communities.

Research Web
Google Scholar
A man with dark hair pulled back is smiling slightly, wearing a white collared shirt. The background is blurred with hints of green and yellow, suggesting an outdoor setting.

Zhaoxi Zhang

Assistant Professor; Lead, U.TOP Lab

Email: zhang.zhaoxi@ufl.edu

Urban health sensing, participatory AI, human-computer-environment interaction, 3D simulation, urban robotics, and technology-forward urban design methods.

Research Web
Google Scholar
A young man with short black hair, wearing a black suit, white shirt, and maroon tie, smiles in front of a plain white background.

Vivian Wong

Assistant Professor

Email: vivian.wong@ufl.edu

Spatiotemporal analysis, machine learning, computer vision, human mobility, urban infrastructure, and simulation of operations and logistics.

Research Web
Google Scholar

Frequently Asked Questions

Common questions about academic background, curriculum pathways, applications, and career direction.

No. The M.S. is structured for students from different academic backgrounds. Students with a planning or similar background may receive a waiver for URP 6007, while students without a planning background take more credits from the Urban and Regional Planning elective group. The Graduate Certificate also has separate pathways for planning-related and computing or engineering-related backgrounds.

No specific computer science background is required for every student. URP 6295 may be waived for students with a computer science or similar background. For students without that background, the detailed M.S. curriculum also recommends introductory programming and data science preparation such as COP 3502C Programming Fundamentals 1 and EEL 3850 Data Science for ECE.

The M.S. requires 30 credits. The current model semester plans distribute those credits across three semesters for both fall-entry and spring-entry students, although an individual student’s schedule can vary based on course availability, waivers, and academic background. The Graduate Certificate requires 15 credits and must be completed within three years of initial enrollment.

The M.S. is a 30-credit graduate degree that includes core urban analytics coursework, planning and machine learning electives, and a 6-credit Master Research Project. The Graduate Certificate is a focused 15-credit credential with two curriculum options based on the student’s prior background.

Yes, in specific cases. URP 6295 may be waived for students with a computer science or similar background, and URP 6007 may be waived for students with a planning or similar background. URP 6223 may be replaced by URP 6931 Artificial Intelligence in the Built Environment with permission from the program coordinator. Alternative electives also require program coordinator approval.

No. The uploaded application requirements for both the M.S. and the Graduate Certificate state that the GRE is no longer required.

For the M.S., applicants submit transcripts, a resume or CV, a personal statement, a statement of intent, three letters of recommendation, and English proficiency documentation when applicable. The Graduate Certificate requires an accredited bachelor’s degree, transcripts, a resume or CV, and English proficiency documentation when applicable. Expand the Application Requirements under each program above for the full details.

Possible job directions include Data Analyst, City Planner, Urban Designer, Consultant, Transportation Planner or Engineer, and Environmental Planner. The exact role depends on your prior degree, technical electives, research focus, internship experience, and any professional credentials required by the employer.

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