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.
Get course updates and notifications
Fill out this form to receive more information and be notified when future courses open for registration.
Course overview
Format:
Online asynchronous
Class size:
Up to 40
Duration:
24 hours across 6 weeks
Course dates:
June 2 – July 14, 2026
Early bird deadline:
May 4, 2026
(use code: MAPDV2 for 20% discount)
Fees:
CAD: $1,249 $999 (HST exempt)
USD: $925 $750
Financial assistance is available through the Ontario Student Assistance Program (OSAP) for Microcredentials. See the OSAP for Microcredentials page for details.
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.
Teaching Team
Jeff Allen, PhD (Content Creator): Senior Research Associate and Lead, Maps & Data Visualization, School of Cities, U of T
Aniket Kali (Facilitator & Assessor): Data Visualization Developer
Course outline
The course spans six modules over six weeks and is fully online and self-paced, featuring asynchronous modules, multimedia content, learning activities, knowledge/progress checks, and weekly assessments.
| Module 1 | Introduction to urban data |
| Module 2 | Data analytics and visualization |
| Module 3 | Spatial data analytics |
| Module 4 | Spatial data visualization 1 |
| Module 5 | Spatial data visualization 2 |
| Module 6 | Bringing it together |
| Assessments | Data analysis, data visualizations, reference & choropleth maps, advanced data-driven maps, presentation |
Testimonials
Hear what recent course participants have to say…
“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.”
“I used power BI to generate charts instead of Excel, with the techniques and feedback from the instructors in this course. Also used spatial data in maps to demonstrate data to make my report more convincing and easy to follow.“
“The most useful aspects were learning to structure clear data narratives and choose effective visualizations. These skills are directly applicable to urban planning and GIS, helping make complex spatial data accessible to decision-makers and the public.”
“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.”
“I really enjoyed learning about GIS and mapping spatial data.”
FAQs
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.
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.
A computer and reliable internet connection are required, and ability to download software onto your computer. Familiarity with basic spreadsheet software is recommended.