Find out more about producing quality research software with Python in part one of this two-part series. This course teaches tools and practices for producing and sharing quality, sustainable and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research.
Difficulty rating: ★★★☆ Intermediate
Who is it for?
- Postgraduate research students and early career researchers who want to develop software to support their research.
- Researchers with foundational software training who wish to refresh and improve their software practices.
Check out a few example learner profiles to see if this course is a good fit for you.
Summary of the topics covered
- Key principles of open and reproducible research and their implications for research software development.
- Analysing software for maintainability, reproducibility and reuse, identifying risks and opportunities for improvement.
- Applying professional software development workflows for version control, reproducible environment management and collaboration.
- Designing modular and extensible software to support reuse and scalable development.
Prerequisites
Foundational knowledge of the following is required to be able to understand code examples used in the course:
- Python used to write scientific code
- Version control with Git
- Working in a command line interface
Duration
7 hours
Next course
25 & 26 November 2026 13:00 - 16:30 (attend both sessions)
Book here
Can't attend?
We don’t have online materials for this session, but the course will run again — so you’ll be very welcome to join next time.