R for Health Data Science
R is a free and versatile statistical programming language, and a popular choice for health researchers, including those in Bristol Medical School. However, its scope can be overwhelming for those still building confidence with the basics. This course builds on foundational skills, introducing key tools for handling, analysing, and presenting health data in R efficiently and reproducibly.
New pilot short course
Initially pilot courses are only open to a limited number of University of Bristol staff and postgraduate research students, who provide detailed feedback in exchange for early access to the course. Find out more about pilot courses
| Dates | 11-12 February 2027 |
|---|---|
| Fee | £0 |
| Format | Online |
| Audience | Open to a limited number of University of Bristol staff and postgraduate research students only (prerequisites apply). |
| Organisers | Dr Ahmed Elhakeem, Eleanor Walsh and Dr Maria A Hernandez Velandia |
Course profile
The aim of this course is to equip participants with practical tools in R for carrying out efficient and reproducible quantitative data analysis, covering the whole analysis workflow from setting up an R project to producing publication-ready outputs.
Please click on the sections below for more information:
This course will be delivered online over 2 consecutive full days. All sessions are live and include short lectures, live coding demonstrations, and supported hands-on practicals. Participants are expected to attend both days in full. Course materials, including code and practical exercises, will be provided.
By the end of the course, participants should be able to:
- set up a well-organised, reproducible R project for a research analysis;
- use the tidyverse and related packages to import, explore, clean, and transform data, including working with dates and character strings;
- write user-defined functions and use iteration to efficiently run repeated analyses (e.g. multiple models);
- produce publication ready tables and figures;
- generate reproducible reports using Quarto, a next-generation publishing system related to R Markdown; and
- use AI tools appropriately to support R coding, and identify where to find further resources and help.
The course is intended for people who want to develop their R programming skills, but who are not yet experienced R users. It focusses on using R to handle and present data efficiently and reproducibly, rather than on statistical analysis methods. Participants are expected to have attended the Introduction to R short course or have an equivalent level of experience with R and RStudio. This course is not suitable for people complete beginners or for advanced R users.
This course will cover:
- setting up reproducible R projects;
- the “tidyverse” and related packages;
- data exploration and wrangling, including dealing with dates and character strings;
- writing user-defined functions and efficiently running multiple models;
- generating publication-ready tables, figures and reports; and
- using AI tools to support R coding.
The course organisers are Dr Ahmed Elhakeem, Eleanor Walsh and Dr Maria A Hernandez Velandia.
Please ensure you meet the following prerequisites before booking:
| Eligibility | This course is available to University of Bristol staff and postgraduate researchers only. Candidates must be able to fully attend the course and provide feedback. |
|---|---|
| Knowledge |
Participants should already be familiar with the basics of R and R Studio, for example, installing and loading packages, importing a dataset, and working with data frames. We recommend attending the Introduction to R short course (or a similar introductory course) before enrolling. |
| Software |
Practical sessions will use Posit Cloud, a free web-based version of RStudio. No installation is needed, but you will need to create a free Posit Cloud account, and we will provide a link and setup instructions before the course. Alternatively, if you have R and RStudio on your own computer, you are welcome to use these if you prefer (a recent version of R is recommended). See R Installation Instructions for further information. |
| Conditions |
Pilot courses are extremely popular and all live sessions must be attended in full. You should only book onto this course if you are able to commit to attending in full and have time to provide detailed feedback. Attendance is monitored. Failure to attend in full, without a valid reason, will result in your access to pilot course materials being rescinded and you will not be permitted to attend any further pilot courses within the same academic year. |
| Recommendation |
We recommend using two screens, or a large screen, so that you can complete the practical work alongside viewing the live sessions. A stable internet connection is required, as all sessions are delivered live online. |
Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.
Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms and conditions, which can be read in full here.
For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.
Participants are granted access to our virtual learning platform (Blackboard Ultra) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.
To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.
All course participants retain access to the online learning materials and recordings for 5 months after the course.