Data Science for Transport Planning: 2 day course
1 Course Overview
Based on demand, we’re organising a 2-day course teaching modern data science skills for transport planning, focussed on transport planning practitioners. This course will take place on the 18th and 19th of September 2025.
2 Prerequisites
- Experience with transport planning concepts and datasets, such as origin-destination data and route networks.
- Basic programming skills in R, Python or similar.
- A laptop with R and RStudio (recommended) or a Python distribution such as Anaconda and an editor such as VS Code or Jupyter Notebook set-up.
3 Schedule
3.1 Day 1: Introduction to R/RStudio
- 10:00 - 11:00 Introduction to Data Science for Transport Planning
- 11:00 - 12:30 Finding, importing and cleaning transport datasets
- Origin-destination datasets
- OpenStreetMap (OSM) and Ordnance Survey (OS) OpenRoads datasets
- Stats19 road safety data
- 12:30 - 13:30: lunch
- 13:30 - 15:00 Origin-destination data analysis
- 15:00 - 15:15 break and refreshments
- 15:15 - 17:00 Routing and route network analysis
- This will cover setting up an OpenTripple API and using it to calculate routes and distances using GTFS data.
3.2 Day 2:
Course times each day:
- 09:00 - 10:45 spatio-temporal data
- Demonstration of open-access OD data with hourly resolution
- Demonstration with stats19 data for road safety analysis
- 10:45 - 11:15 break and refreshments
- 11:15 - 12:30 OD Transport data visualisation
- 12:30 - 13:30 lunch
- 13:30 - 15:00 Best practices for data science in transport planning
- Version control with Git and GitHub
- Reproducible research with Quarto
- 15:00 - 16:00 Advanced topics
- Visualising large datasets
- Route network integration
- We’ll present ways to join different networks, e.g. OSM networks
- Deploying your work as web applications
4 Registration
TBC.
We look forward to seeing you at the course!