Training.

Technical AI training for data and engineering teams. Building sustainable in-house development expertise.

§ 01 Proposition

Training built around the room, not around a curriculum.

Training programs designed around who's actually in the room — leadership briefings, hands-on workshops for engineers and analysts, mixed-team sessions when the question crosses both. Single days or single workshops, not long programs.

Curriculum is built per engagement: AI fundamentals, prompt engineering, RAG and agents, building AI into products, data literacy, change management, AI strategy. The format follows the room — in-person, virtual, or both.

§ 02 Principles
  1. 01

    Audience-specific

    Leadership briefings sound different from engineering workshops. We build the curriculum around who's actually in the room.

  2. 02

    Hands-on first

    Concepts presented, then practiced. Real prompts, real datasets, real tooling — knowledge that survives the training day.

  3. 03

    In-person or virtual

    Single-day in-person sessions, half-day virtual workshops, or a mixed series. Whatever fits how the team actually works together.

  4. 04

    Train your trainers

    Internal AI champions trained to keep the learning going after we leave. Shorter follow-up sessions when the team is ready.

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