R for Health Data Science Research
This course will lead the students through a project analysis lifecycle, from importing data, setting up reproducible code in R, data cleaning and transformation, efficiently running (many) models and generating publication standard tables, figures and reports.
Students will learn about the grammar of graphics, literate programming, and reproducible research to save time when wrangling, visualizing, and exploring data.
This course will introduce students to R packages that can support their work (predominantly tidyverse), rather than just relying on base R. Teaching will be a mix of live short lectures illustrated by demonstrations in R, interspersed with longer practical sessions where students will work in breakout rooms.
New pilot course for 2026-2027
We are excited to be developing this new pilot short course for the 2026-2027 programme. 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.
Please bear with us whilst we update this course webpage with full course details.
| 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. |
| Organisers | Dr Ahmed Elhakeem, Eleanor Walsh, Dr Maria A Hernandez Velandia |
Course profile
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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 & 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.