Computer Science · Professional
Research Software Engineering & Reproducible Science
Turn scripts into reliable, shareable research tools — packaging, testing, version control, dashboards and APIs.
Course modules
- 01Git, GitHub and collaborative workflows
- 02Project structure, packaging and environments
- 03Testing, documentation and code quality
- 04Databases and SQL for research data
- 05Dashboards and simple web apps (Streamlit)
- 06Open science: licences, DOIs and data sharing
Learning outcomes
- Publish reproducible, citable code
- Build a small research app or dashboard
- Collaborate effectively on code
Project-based training
Every participant completes a capstone: Open science: licences, DOIs and data sharing. Labs use real environmental, agricultural or engineering datasets.
Tools
- Git
- Python
- pytest
- SQL
- Streamlit
Who it’s for
Researchers, PhD scholars, technical staff
Prerequisites
Python basics
