Centre for Research Informatics Training
BBSRC (AY2627)
This page lists the training events assigned to your cohort.
| Event | Start date | Status | |
|---|---|---|---|
| Data analysis in R | Tue, 12 Jan 2027 | ||
| Reproducible research | Thu, 14 Jan 2027 | ||
| Visual data communication | Fri, 15 Jan 2027 | ||
| Core statistics | Mon, 19 Apr 2027 | ||
| Principles of Machine Learning | Thu, 22 Apr 2027 |
Additional information
Most sessions will consist of a mix of lectures, interactive practicals and self-paced computational exercises.
Access to canonical lecture recordings are available for Data analysis in R, Core statistics on request by emailing the administration team
Before each event
Please ensure that you arrive 10 minutes before the start of each session. Times and locations are available on the event-specific pages linked above.
Please review relevant prerequisites on event-specific pages before each module.
Introductions
Please introduce yourself to the trainers so that they have a better understanding of their audience and your background. You can do this in the introductions document.
Course materials
- Data analysis in R (online course materials, slides (TBC))
- Reproducible research (online course materials, slides (TBC))
- Visual data communication (online course materials), slides (TBC))
- Core statistics (online course materials, slides (TBC))
- Principles of Machine Learning (online course materials (TBC), slides (TBC))
If joining any open courses, joining instructions and links will be provided separately.
Software
You will have access to full loaded computers in the training room. However, we encourage you to bring your own laptops (fully charged) to the sessions to make sure that you have the correct software loaded and are able to continue learning in your own time.
Please ensure that you have installed any required software (below) prior to the course and that you have admin rights on the laptop to install additional programmes if needed. Installation instructions can be found in the course materials or using the required software links below.
- RStudio/R and tidyverse Installation instructions
Required for the Data analysis in R and Core statistics modules. Install the software following installation instructions.
- Reproducible research R/Studio Installation instructions | Pre-course Github preparations
Ensure that you have R/Studio and git installed on your laptop following the instructions links above. Please ensure that you have a GitHub account and remember to bring your authentication device (fully charged phone) that you used to set up 2-Factor Authentication.
- Visual data communication and Principle of machine learning require you to use your own machine. Please bring your laptop (fully) charged to each session.
Feedback survey
Please give us feedback after each module! This will help us shape future iterations of the course.
Looking for additional training
Sign up to our mailing list to get notification of upcoming courses.
Timetable of the upcoming CRIT courses.
Information updated 2026-09-03