Centre for Research Informatics Training
Reproducible research
Not yet bookable
Event details
Sessions
- 14 January 2027 — 09:30 to 17:30 — Craik-Marshall
Book this event
This event is not yet bookable.
About the course
A practical introduction to reproducible research workflows using R, R Markdown and GitHub.
Reproducibility is an essential component of modern computational research. This course introduces practical tools and workflows that help researchers organise analyses, document their work and collaborate effectively on shared projects.
Participants learn how to create dynamic notebooks and reports using R Markdown, combining code, results and written interpretation within a single document. The course also introduces version control using Git and GitHub, enabling participants to track changes, manage project histories and collaborate without creating conflicting file versions.
By the end of the course, participants should be able to:
- understand the importance of reproducible computational workflows
- create notebooks and reports using R Markdown
- combine code, figures and written interpretation within reproducible documents
- understand the principles of version control using Git
- create and manage repositories on GitHub
- collaborate on shared projects using version control workflows
Teaching is primarily hands-on, combining presentations, demonstrations and guided practical exercises.
Intended audience
This course is suitable for:
- researchers and students working with computational or data analysis workflows in R
- participants interested in improving the reproducibility and organisation of their research projects
- researchers who want to learn collaborative coding and version control practices
- participants looking to integrate analysis, figures and reports into reproducible documents
Prerequisites
Participants should have basic familiarity with R programming before attending this course.
Previous experience creating analyses or scripts in R is recommended, although prior knowledge of Git, GitHub or R Markdown is not required.
Course fees
All fees are per full training day
| Category | Fee |
|---|---|
| Industry full charge | £130.00 |
| Academic / Government / charity concessionary | £65.00 |
| Cambridge University staff members / postdocs / visitors | £65.00 |
| Cambridge University registered students | Free |
| Special events | Per event |
Payment options will be provided in booking confirmation emails sent after registration.