AI

AI Product Manager

Structured training in scoping and shipping AI-powered products — bridging technical teams and business goals without needing to build the models yourself.

50
hours of live training
10 weeks
at one hour a day, weekdays
4
modules
24
topics covered

Before you start

Some professional background helpful. If you are not sure whether that describes you, the consultation exists to answer exactly that — and to tell you if a different programme is the better start.

Price

United Kingdom
£750
Canada
$1,750

Tax included — the price shown is the price you pay. This covers the training stage. The bootcamp and placement stages are priced separately.

Curriculum

A module-by-module breakdown

Everything covered in the program, in the order you'll cover it.

01What AI Can and Cannot Do

12 hours

Enough technical grounding to make good calls

  • Model families & their trade-offs
  • Where ML fits a product and where it does not
  • Reading model evaluation metrics
  • Data requirements & labelling cost
  • Latency, cost & quality triangle
  • Talking credibly with ML engineers

02Discovery & Scoping

13 hours

Choose the right problem before building

  • Opportunity sizing for AI features
  • Writing an AI product requirements doc
  • Success metrics & offline/online evaluation
  • Human-in-the-loop design
  • Failure modes & graceful degradation
  • Build, buy or fine-tune decisions

03Delivery & Iteration

13 hours

Ship it and improve it

  • Roadmapping under model uncertainty
  • Prompt & model versioning as product surface
  • A/B testing AI features
  • Feedback loops & data flywheels
  • Managing stakeholder expectations
  • Pricing & packaging AI capability

04Risk, Ethics & Governance

12 hours

The part that stops a launch being reversed

  • Bias & fairness assessment
  • Privacy & data residency
  • EU AI Act & emerging regulation
  • Model cards & documentation
  • Incident response for AI failures
  • A capstone product case & pitch

Projects

Five projects, in AI Product Manager

The bootcamp runs the same five stages whatever you enrolled in, so the portfolio you finish with is deep in one technology rather than shallow across several. Each is scoped, designed, built and reviewed.

  1. 01 · Foundations

    A first build that puts the core concepts to work — environments configured, the basic workflows exercised, the fundamentals proven rather than assumed.

  2. 02 · Multiple moving parts

    A larger solution with several components and an integration or two, applying the practices that are conventional in your stack rather than improvising.

  3. 03 · Architecture that scales

    A design-led build: scalability, monitoring and the production-grade patterns your field actually uses, decided before they are implemented.

  4. 04 · An enterprise scenario

    A realistic situation with services that depend on each other, security to harden and performance to tune — the kind of work that is waiting on the other side of the offer.

  5. 05 · Capstone

    End to end, everything together: planned, designed, built, deployed and documented well enough to sit at the top of your GitHub profile.

What's included

Everything in the programme

The same seven things in every programme on the site — the subject is what changes.

  • Live training

    Taught live by a practitioner, not pre-recorded video you work through alone.

  • 50 hours

    Per programme as standard — 60 for IT Support Analyst, 70 for the AI Consultant and cloud engineering tracks.

  • Projects

    Five briefs in your own stack, each scoped, designed, built and reviewed the way a delivery team would.

  • Mentoring

    One mentor who stays with you for the whole programme, rather than whoever is free that week.

  • Resume & LinkedIn

    Both rewritten around the work you actually built, and positioned for the roles you are targeting.

  • Interview prep

    Mock interviews on the technical and the competency side, including defending the projects you built.

  • Placement support

    Your profile put in front of employers, and the search continues until you are hired.

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