Three formats, one path. Each program builds on the last – so you can start small without starting over.
GenAI for data scientists
The entry point. From single LLM calls to structured AI workflows, in one day.
Practical GenAI for data scientists
Everything from day one, then applied to your own datasets and real business problems.
RAG + practical GenAI
The complete program. Adds a full day of retrieval-augmented generation on company data.
Day 1: Foundation
Field update, agent coding, integration patterns, evaluation basics
Day 2: Applied
Your datasets, your problems, agentic development with Claude Code
Day 3: Production
RAG pipelines on company data, reasoning and retrieval evaluation
1 Day: GenAI for data scientists
The entry point. Move from single LLM calls to designing structured AI workflows - in one day, with no prior GenAI experience needed. Best for teams evaluating GenAI adoption who want a low-risk pilot.
2 Day: Practical GenAI for data scientists
Everything from day one, then applied to your own datasets and real business problems. Day two adds agentic development with Claude Code. Best for teams that want capability on their actual work, not general familiarity
3 Day: RAG + practical GenAI for data scientists
The complete program. Adds a full day on retrieval-augmented generation - designing, implementing, and evaluating RAG pipelines on company data. Best for teams committing to a full AI capability build
No. Each format is self-contained – the longer programs include all the content from the shorter ones. Teams with existing hands-on GenAI experience may move faster through the foundational days, which we can adjust during the discovery phase.
Yes, to varying depth. The 1-day format includes a discovery phase to align with your team’s maturity and tooling. The 2-day format builds day-two exercises around your own datasets. The 3-day format is the most deeply customised, with both days two and three built around your organisation’s data and problems.
The main question is what you want the team to be able to do afterwards. General capability with GenAI patterns points to the 1-day. Working solutions on your own problems points to the 2-day. Systems that retrieve and reason over your company’s documents point to the 3-day.
Participants should be comfortable with Python and the command line, and have prior data science experience. No prior GenAI or LLM experience is required for any of the three formats.
We combine engineering discipline with architectural thinking. The focus is realistic system behaviour, common failure modes, cost, and production readiness – not on how to build an impressive demo. Our instructors are practitioners.
Pricing depends on group size, format, and the depth of customisation. Request a proposal and we’ll send a written quote, valid for 90 calendar days.
You may cancel or reschedule free of charge up to three weeks before the scheduled date. Any preparation work already completed may be charged in the case of a late cancellation.
Equip your data scientists to build with GenAI responsibly, at production scale.