Private courses for your team
We run courses privately for your team, using your datasets and the problems your people work on. Examples built on your own data are the ones participants keep using after the course.
Each trainer takes up to twelve participants. In a group that size, the trainer can look at the code on your screen and help you fix it, which a recorded video cannot do. For larger groups we bring additional trainers, so the ratio holds however many people you send.
Any of our courses can run this way. We also design new ones. We start from what your team already knows and what they need to be able to do, and build the course to cover the difference. If a subject is outside our expertise, we bring in specialists and work with them.
Some courses need groundwork first. In that case we take on consulting work to understand your systems and develop the material.
Get a quoteWhy teams book privately
- Up to 12 participants per trainer. Send a bigger group and we add trainers to keep the ratio.
- Your data. On request we teach with your datasets and code bases, so your team recognises the worked examples.
- One shared approach. The whole team learns the same methods, and senior staff help juniors while learning themselves.
- One booking. One date and one invoice, instead of booking seats one at a time across a dozen calendars.
- Your schedule. At your office or online, and split across days or weeks if that suits the team.
Better than a team-building day
A team that spends two days solving real problems together gets what an offsite is meant to deliver, and leaves with working code as well. Colleagues who rarely compare notes often find they have been solving the same problem twice, in different ways.
Mixed experience levels help. Senior staff test their own understanding by explaining it, and junior staff ask questions a set syllabus would not anticipate. Everyone leaves with the same vocabulary, and the same worked examples to refer to in code review.
Private training also works across teams. Analysts and engineers who take a course together tend to stop handing each other work in formats the other has to undo.
How it works
Tell us what you need
A short conversation about what your team does now, what you want them doing, and how much Python they already write.
We design the course
You get an outline to review before anything is booked, built from our material and yours. Change it as much as you like.
We run it
At your office or online, on dates that suit you. Participants write code in every session, rather than sitting through slides.
Afterwards
Participants keep the course materials and notebooks, and can bring questions to our open office hours.
Popular custom training topics
Python fundamentals
Data types, control flow, functions, and the practices that keep code readable six months later. This topic is pitched at people who already work with data in Excel or another language, so it moves faster than a beginners' course. We teach current Python throughout, not the idioms of a decade ago.
Data analysis, science & engineering
Cleaning, reshaping and joining data with pandas or Polars, then visualising it and reporting on it. We cover the statistics behind the methods, so you can say why a result should be trusted. We also cover the engineering that turns a working notebook into a pipeline that runs on a schedule without someone watching it.
Machine learning, deep learning & artificial intelligence
Choosing a method that suits the problem, training a model, and measuring whether it is any good. We spend as much time on evaluation and failure modes as on fitting, because that is where deployed models disappoint. Taught by PhD-level trainers who have put these models into production.
Python for DevOps
Automation, scripting and API development for people who keep systems running. This covers replacing shell scripts that have grown too large, calling the APIs of the tools you already use, and testing the result so an unattended job fails loudly rather than silently.
LLM development
Prompting, retrieval-augmented generation, fine-tuning, and the engineering around a language model in a real application. This includes how to evaluate output that differs on every run. Evaluation decides whether a prototype holds up once real users reach it.
Something not listed here
We have taught across finance, science, government and engineering for fifteen years, so most requests are close to something we have taught before. Where they are not, we find the experts and build the course with them. Tell us the problem and we will tell you honestly whether we are the right people.
Every course here started as someone's specific problem.
Discuss your requirementsTalk to us about your team
Tell us what your team works on and how many of them there are. We will come back with an outline and a fixed price, usually within two business days.
Request a quote