Webinars and Workshops
Please note:
- Workshop attendance is restricted to UK employees of the NHS, public sector, civil service, voluntary sector, charities and academia, or who are retirees from any of these sectors. Please note you must sign up with a work email address to verify your credentials.
- Webinars are free to all to attend, and recordings are stored on our YouTube Channel
April 2026
📆 28th & 29th Intermediate R with Dr Claire Welsh:
This course is designed to follow on from the Introduction to R and RStudio course, noting that attendees should be familiar with the basics covered in the workshop. Please be advised that this session will go into more depth and complex wrangling tasks, explore how to use the NHS-R SPC plot the dots library and cover in very simple terms an understanding of some functional programming. This workshop will utilise the cloud, with all datasets provided as part of the course material, so no specialist set up is required.
- Workshop - limited to 25 attendees
- 09:00 - 13:00 (GMT)
- 🔗 Request a place on the course here
May 2026
📆 21st Building Reproducible Pipelines for Open Health Data: From Ingestion to Geographical Analysis and Visualisation with Mattia Ficarelli, PhD:
This webinar will explore how to design reproducible, automated pipelines for working with open health data, covering data ingestion, reuse of public datasets, and scalable approaches to processing and analysis. It will focus on managing geographical complexity, including mapping across NHS and statistical geographies over time, and demonstrate practical methods for analysing and presenting results clearly.
- Webinar
- 13:00 - 14:00 (GMT)
- 🔗 Register to attend here
June 2026
📆 18th Building a Reproducible Analytical Pipeline (RAP) for Simulation with Python and R with Amy Heather:
Reproducible Analytical Pipelines (RAPs) are becoming essential in the NHS for producing transparent, trustworthy analysis and modelling at scale. In this webinar, we’ll walk through a full RAP built around a discrete‑event simulation (DES) model, using examples from the DES RAP Book (https://pythonhealthdatascience.github.io/des_rap_book/). We’ll show how we created DES models in both SimPy (Python) and simmer (R), while meeting the NHS Levels of RAP criteria at gold status. We’ll highlight practical steps you can take to make your own work more reproducible and robust.
- Webinar
- 13:00 - 14:00 (GMT)
- 🔗 Register to attend here