Urban environments generate a wealth of data that can drive impactful decisions and policies. However, the challenge often lies in processing and visualizing this data to make it understandable and actionable. This course provides a deep dive into urban data sources, analytical tools, and visualization techniques.
You will work with a range of analytical and visualization tools—including GIS, spreadsheet software, and other data platforms—to build your technical skills and apply them to real urban challenges. While this is a technical course, it is not focused on teaching you how to use all the tools listed. The emphasis is on application and interpretation: understanding which tools to use, how to structure your analysis, and how to create effective visual narratives for professional audiences.
Course overview
Duration:
7 hours per week (exclusive of assignments)
Size:
Up to 40
Format:
Online asynchronous
Fees:
Regular: CAD $1,249
Early-bird: CAD $999
Course dates:
Sept 9 – Oct 21
Oct 27 – Dec 8
Early-bird deadline:
—
September 28 (use code 2MAPDV)
Register by:
August 31
October 19
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What you’ll learn
Ready to go deeper with tools and analysis? This course equips you to:
- Find and collect urban data on a variety of topics and from a range of sources that can help inform decision and policy making
- Use Geographic Information Systems (GIS), spreadsheet software, and the programming language Python to process, explore, and analyze data
- Create different types of maps and visualizations to effectively communicate data to a variety of audiences
Intro video
Course outline
The course spans six modules over six weeks and is fully online and self-directed, featuring asynchronous modules, multimedia content, learning activities, knowledge/progress checks, and assessments. (click below to expand)
Module 1: Introduction to urban data analytics
- Introduction to urban data analytics and urban data storytelling.
- Urban data sources, types, and formats, including census data
- Applications of urban data in understanding urban issues and informing decision-making
- Data interpretation, representation, visualization, and bias in urban data analysis
Module 2: Data analytics & visualization
- Principles and purposes of data visualization for exploring and communicating information
- Visual design concepts, including visual variables, perception, cognition, and accessibility
- Evaluation of charts and graphs for clarity, accuracy, and effective communication
- Selection and interpretation of common visualization types, including bar charts, line charts, scatter plots, histograms, area charts, and density plots
Module 3: Spatial data analytics
- Fundamentals of spatial data, including spatial thinking, geographic data types, spatial units, coordinate reference systems, and data formats
- Introduction to GIS and QGIS for loading, visualizing, and managing spatial datasets
- Core spatial analysis techniques, including geocoding, buffering, centroids, spatial selection, spatial joins, and overlay operations
- Data quality, limitations, and critical evaluation of spatial data in urban research and decision-making
Module 4: Spatial data visualization
- Principles of cartographic design, including map purpose, classification, symbolization, colour, and layout
- Types of maps and their applications in urban data visualization, including thematic and reference maps
- Creation and styling of spatial visualizations in QGIS using vector and raster data
- Development and evaluation of choropleth maps and other thematic maps to communicate spatial patterns and support urban data storytelling
Module 5: Descriptive statistics and advanced spatial data visualization
- Advanced urban data visualization techniques, including proportional symbol maps, bivariate maps, flow maps, and categorical dot maps
- Principles for selecting and designing effective visualizations to communicate spatial patterns and relationships
- Descriptive statistics and introductory statistical analysis, including measures of central tendency, correlation, regression, and hypothesis testing
- Integration of statistical analysis and data visualization to support evidence-based storytelling and interpretation of urban phenomena
Module 6: Advanced urban analytics and interactive visualization
- Advanced urban analytics concepts, including working with large and complex urban datasets and integrating multiple analytical approaches
- Data storytelling and communication strategies for presenting urban data to diverse audiences
- Interactive visualization formats, including dashboards, web maps, static explainers, and scrollytelling
- Foundations of database management, SQL, and advanced analytical methods for urban research and decision-making
Earn up to 24 Continuous Professional Learning Units
You may also be eligible to earn up to 24 Continuous Professional Learning (CPL) units to maintain your professional certification from your planning institution or association. See the Canadian Institute of Planners website for more information about annual CPL requirements.
Testimonials
Hear what recent course participants have to say…
“The course structure worked well, particularly the balance between short instructional content and practical assignments. The assignments helped reinforce how data techniques can be applied in real urban analysis contexts.”
“The format, organization, and exposure to different tools were really great. I especially liked the fact that the course was tool-agnostic, and our teachers took care to share what was possible with other tools.”
“The course gave me great examples, reference points, and foundational knowledge that made mapping much more accessible. I was able to leverage much of what I learned to support my professional work.”
Teaching team and their work
Jeff Allen, PhD (Course Creator): Senior Research Associate and Lead, Maps & Data Visualization, School of Cities, U of T
Aniket Kali (Facilitator & Assessor): Data Visualization Developer
Frequently asked questions
Do I need prior technical or data analysis experience?
To successfully complete the course assessments, you will need access to both GIS software (such as QGIS) and spreadsheet software (such as Excel or Google Sheets). The course includes basic QGIS instruction, so no prior experience is required. While familiarity with spreadsheets is recommended, we will also provide links to external resources to help you build or refresh these skills. Python is optional and not required for completing the course.
Is this course a standalone credential or part of a larger program?
It can be taken as a standalone micro-credential. Alternatively, combined with the companion course (Urban Data Storytelling) it contributes toward the full certificate program in data analysis & storytelling.
What do I need in terms of technology or software to participate?
A computer and reliable internet connection are required, and ability to download software onto your computer. Familiarity with basic spreadsheet software is recommended.
Financial assistance is available through OSAP
Financial assistance is available through the Ontario Student Assistance Program (OSAP) for Microcredentials. See the OSAP for Microcredentials page for details.
Policies for School of Cities non-credit professional learning offerings, including microcredentials, workshops, certificates, and custom training.