Training
Team training, workshops and consulting
The material on this site is free to use. This page describes the delivered formats — live training, workshops and consulting engagements — for teams that want more than self-study.
Rates, availability and specific offerings are placeholders. Replace them with your own terms before publishing.
Formats
Format 01
Instructor-led course
The full course delivered live over several sessions, with your own data used for the exercises. Recorded if you want it. Typically 4–6 half-day sessions per course, 6–12 participants.
Format 02
Focused workshop
One or two days on a specific topic — admiral derivations, Shiny modules, metadata-driven programming, testing and validation. Hands-on throughout, with a working deliverable at the end.
Format 03
Migration support
Planning and hands-on support for a SAS-to-R transition: environment setup, standards package development, parallel running, and the evidence a quality function will ask for.
Format 04
Code review and mentoring
Ongoing review of your team’s R or Python code, with written feedback and pairing sessions. The fastest way to raise the standard of code a team actually writes, as opposed to the code they write during training.
Suggested programmes
For a team new to R
| Week | Content | Format |
|---|---|---|
| 1–2 | R Programming lessons 1–7 | 4 half-day sessions |
| 3 | Guided practice on your own data | Workshop |
| 4–5 | R Programming lessons 8–12 | 3 half-day sessions |
| 6 | First real deliverable, supervised | Pairing |
| Ongoing | Code review | Fortnightly |
For statistical programmers moving from SAS
| Week | Content | Format |
|---|---|---|
| 1–2 | R Programming, condensed | 4 half-day sessions |
| 3–4 | Clinical Programming lessons 1–5 | 4 half-day sessions |
| 5 | Reproduce a completed study’s ADaM in R | Workshop |
| 6–7 | Clinical Programming lessons 6–10 | 4 half-day sessions |
| 8 | Reproduce that study’s TLFs, compare to SAS | Workshop |
| Ongoing | Parallel running support | As needed |
Reproducing a completed study is the single most effective exercise in this programme. There is no delivery pressure, the correct answer is known, and every difference between the R and SAS output is a learning opportunity rather than a crisis.
For a team building internal tools
| Week | Content | Format |
|---|---|---|
| 1 | R Programming lessons 8–12 (functions, testing, packages) | 3 sessions |
| 2–3 | R Shiny lessons 1–6 | 4 sessions |
| 4 | Build a real tool for your team | Workshop |
| 5 | R Shiny lessons 7–11 (auth, testing, deployment) | 3 sessions |
| 6 | Deploy it properly | Pairing |
What is included
- All course material, yours to keep and reuse internally
- Exercises adapted to your data and therapeutic area
- Session recordings, if wanted
- A written summary after each engagement: what was covered, what to do next
- Follow-up questions by email for a defined period
What is not included
Honesty is more useful than a longer list:
- Certification. There is no accredited certificate. If your organisation requires one, this is not it.
- Validation of your environment. Training does not validate anything. The courses cover what validation requires; performing it is your quality function’s responsibility.
- A guarantee that R is right for you. The migration lesson sets out when not to migrate, and that advice is given in engagements too.
Practical details
Delivery — remote, on site, or hybrid. Remote works well for the taught sessions; workshops benefit from being in a room together.
Group size — 6 to 12. Below 6 the discussion thins out; above 12 the hands-on portions stop working.
Prerequisites — stated per course. The main one is that participants have working R installations and the ability to install packages before day one. An hour lost to IT problems on the first morning is an hour lost for everyone.
Materials — participants use this site during and after the training, so there is no separate handout to lose.
Getting started
The most useful first conversation covers:
- What your team does now, and in what tool
- What is driving the change
- What has to be delivered, and by when
- What your quality function will require
- How much time the team can genuinely protect for learning
That last question determines more than any of the others.
Get in touch to arrange it.