Data Science for Transport Planning
Note: Tickets are now sold out
Learning Objectives
- Understand the role of data science in transport planning.
- Learn how to find, import, clean, and analyze transport data.
- Develop skills in data visualization and reporting.
Registration
See store.leeds.ac.uk for registration details.
Data Science for Transport Planning
This is the source repository for the Data Science for Transport Planning (DSTP) course website.
The DSTP course is a 2-day intensive course on data science skills for transport planning practitioners, scheduled for 18-19 September 2025 at the University of Leeds.
Visit https://tdscience.github.io/dstp/ to see the rendered website.
Course Overview
This course teaches modern data science skills tailored for transport planning, including data acquisition, cleaning, analysis, visualization, and reproducible reporting. It focuses on practical applications using R and Python, with real-world transport datasets.
Prerequisites
- Basic knowledge of transport planning concepts and datasets
- Familiarity with programming in R or Python
- A laptop with R (essential), Python (optional) and a data science IDE such as RStudio (recommended), VS Code or Positron installed
- A GitHub account (a GitHub account should allow you to run the code in the cloud via GitHub Codespaces as a fallback if needed)
See the prerequisites page for detailed setup instructions.
Schedule
The course covers 7 sessions over 2 days. See the schedule page for details.
Technical Information
The repository structure is as follows:
s1.qmd
tos7.qmd
: Course session materialsdata/
: Sample datasets used in the coursetds/
: Additional transport data science materials and projects.devcontainer/
: DevContainer configuration for consistent development environment.github/
: GitHub Actions workflows for publishing
Running Locally
This project uses Quarto to generate the website. To run locally:
- Install Quarto: https://quarto.org/docs/get-started/
- Clone this repository
- Open in VS Code with DevContainer support (recommended)
- Run
quarto preview
to preview the site
Alternatively, use the “Open in Codespaces” button above for an instant cloud development environment.
Contributing
Contributions are welcome! Please:
- Open issues for bugs or feature requests
- Submit pull requests for improvements
- Join the GitHub Discussions for questions
License
This project is licensed under CC BY-SA 4.0. See LICENSE for details.
Contact
For course inquiries: Robin Lovelace
Repository maintainer: Robin Lovelace