This repo contains code to support teaching the use of data science and AI and Data Science for Transport planning. By AI we mean services such as Google Gemini, ChatGPT and similar tools from web user interfaces and APIs to:
- Automate boring tasks
- Speed-up work to increase productivity
- Enhance capabilities, leading to new and better outputs
The ultimate goal is more effective transport planning investments and decisions
Python Environment Setup
Some Quarto documents in this repository utilize Python code. To ensure these documents render correctly, it’s recommended to set up a Python virtual environment and install the necessary dependencies.
- Create a virtual environment:
bash python3 -m venv .venv - Activate the virtual environment (Linux/macOS):
bash source .venv/bin/activate(On Windows, use.venv\Scripts\activate) - Install dependencies:
bash pip install pandas matplotlib numpy osmnx geopandas shapely openai requests pypdf ipython jupyter openpyxl tabulate jupyter-cache
The trigger for the course was interest from Transport for the South East (TfSE) in using AI to improve transport planning. See the tfse document for the (currently in-development) course content for that specific course.