This course is designed for researchers who want to develop reusable and reproducible workflows in R and RStudio. It focuses on the practical challenges that arise when writing reproducible R code: ensuring that others can successfully re-run your analyses, and validating that your code behaves as intended. Throughout the course, we emphasise best practices for producing modular, readable, well-documented, and well-tested R code. Whether you are new to writing structured R programs or simply want to improve the quality and maintainability of your analyses, this course will help you adopt methods that make your work more reliable and reproducible.
Difficulty rating: ★★★★ Advanced
Who is it for?
Both research staff and research students
Summary of the topics covered
- Create an R project that generates reproducible outputs
- Use best practices for developing reproducible R code, i.e. apply techniques to ensure that your code is modular, readable, and well documented
- Implement unit tests to check that your code is working as expected
- Manage project dependencies using a reproducible environment (renv)
Prerequisites
Learners should have at least six months of experience using R.
Frequency
1 time a year
Duration
7 hours (over 2 half days)
Next course
10th (09:30 - 13:00) & 11th (13:00 - 16:30) February 2026
Book here
Can't attend?
Course materials available : https://bham-carpentries.github.io/2025-03-11-r-advanced/01-introduction.html
User Group
There is an R user group with links to resources and contacts.
Help with R
If you need help with using R, you can contact our Research Software Group for advice. You can also raise a ServiceDesk ticket with us, or attend one of our drop-in sessions.