Summary and Setup
This is a new lesson built with The Carpentries Workbench.
An intermediate-level practical course on integrating Artificial Intelligence (AI) tools into research software development. Building on foundational knowledge of large language models (LLMs) and AI coding assistants, this course focuses on using these tools effectively within integrated development environments (IDEs).
Researchers will develop practical skills to enhance productivity, improve code quality, and apply AI responsibly in real-world research projects.
These training materials are adapted from “Developing Research Software with AI Tools” developed by the Southampton Research Software Group under CC-BY 4.0
The development of the original course at Southampton was funded through the EPSRC Doctoral Landscape Award EP/Z534894/1 2025 additional skills funding underpinning the pipeline for AI skills.
Changes to the original materials are recorded in ATTRIBUTION.md.
Skills Prerequisites
The following are necessary to be able to participate in this course:
- You have a basic knowledge of programming in Python (using variables, lists, conditional statements, functions and importing external libraries)
- You have previously written Python scripts or iPython/Jupyter notebooks to accomplish tasks in your domain of work
It is also helpful but not necessary to have some basic knowledge of Git version control (cloning repositories, making commits, pushing to a remote repository).
Software Setup
To go through the course material on your own or at a workshop, you will need the following accounts set up and software installed and working correctly on your system:
- Command line terminal (shell) (such as Bash, Zsh or Git Bash)
- Git version control tool
- Python 3
- Visual Studio Code (VS Code) integrated development environment (IDE)
- GitHub account, and
- inflammation data and analysis code which we will be used for exercises in the course.
Please follow the installation instructions to install the above tools and set up for the course.