Your team doesn't need another webinar. They need someone who has actually trained models and shipped AI systems to stand in the room, show them how it's done, and answer the hard questions from experience.
We run AI/ML trainings from one to five days — for engineers, for leadership, or for both at once. Hands-on wherever possible: your people leave having built something, not just watched something.
Who This Is For
- Engineering teams that need to go from "we call an API sometimes" to building RAG systems, agents, and evaluations properly
- Leadership teams that need a grounded picture of what AI can do for the business — and a defense against vendor snake oil
- Companies rolling out AI tools who want the whole org on a shared vocabulary before the arguments start
AI Team Training 1–5 days · on-site or remote
A workshop scoped to your team and your goals. Pick a format:
- 1 day — Foundations & strategy. How LLMs actually work, what they can and can't do, where AI pays off in your business. For leadership or mixed audiences.
- 2–3 days — Hands-on building. Prompt engineering, working with model APIs, building RAG systems and agents, evaluating whether any of it actually works. For engineers and technical teams.
- 5 days — Deep dive. The full stack: from prompting through fine-tuning, deployment, and evaluation pipelines. Your team ships a working internal project by Friday.
Curriculum customized to your industry and, where practical, built on your own use cases and data. Priced per format on the intro call.
Topics We Cover
LLM Fundamentals
How language models work under the hood, their real capabilities and failure modes — explained by people who have trained them from scratch.
Prompting & APIs
Getting consistent, useful outputs; structured generation; working with commercial and open-weight models in production code.
RAG, Agents & Evaluation
Building retrieval systems and agents that hold up — and the evaluation discipline that tells you whether your AI is actually working.
Fine-Tuning & Deployment
When fine-tuning beats prompting, how to do it (LoRA to full training), and how to deploy models on your own infrastructure.
Want the training to end with something real in production? Pair it with an AI POC Sprint. Rolling out AI coding tools to your engineers? That's AI Engineering Workflows.
FAQ
Is the training for technical or non-technical audiences?
Both — but not with the same material. We run executive sessions in plain language (what AI can and can't do, where the money is, how to judge vendors), deeply technical tracks for engineers (APIs, RAG, agents, evaluation, fine-tuning), and mixed formats where leadership and engineers build a shared vocabulary. Tell us who's in the room; we build the day around them.
How long is a training and what fits in each format?
From 1 to 5 days. One day covers fundamentals and strategy for one audience. Two to three days adds hands-on building: your people leave having built a working RAG system or agent. Five days is a deep dive through the full stack, from prompting to fine-tuning and deployment. We help you pick the format on the intro call.
Is it hands-on or lecture-style?
Hands-on wherever the audience allows it. Engineers write code from hour one and leave with working projects, not just slides. Executive sessions are discussion-driven with live demonstrations on examples from your own business — we build something in front of you, with your data where possible.
Can you customize the curriculum to our industry and our data?
Yes, and we strongly recommend it. Generic exercises teach less than examples from your own domain. Before the training we review your use cases and, where practical, build the exercises around your industry, your documents, and your actual problems.
Do you run trainings on-site or remote?
Both. We're remote-first with home bases in Brisbane and Berlin and travel for on-site trainings worldwide. Multi-day hands-on formats usually work best in person; shorter or distributed-team formats work well over video.
Who does the teaching?
The same senior engineers and PhDs who do our consulting work — people who have trained language models from scratch and shipped AI systems to production. You get practitioners answering hard questions from experience, not trainers reciting someone else's deck.
What happens after the training?
You keep all materials, code, and exercises. Most teams follow up with office hours, a second session a few weeks later, or a build engagement where we develop the first real project together — see AI Product Development.
Want your team trained by practitioners?
Book a free 30-minute call. Tell us who's in the room and what they should be able to do afterwards — we'll propose a format.
No pitch deck, no obligation. If AI is the wrong answer for your problem, we'll tell you that too.