Pathways into the AI roles enterprises are hiring for
Live, instructor-led programmes where two-thirds of every session is hands-on. Each pathway ends with a team capstone and a demo, so graduates leave with working systems — not just certificates. Open to individuals, or run privately for your team.
Learn at your own pace
AI Governance Frameworks: NIST AI RMF, ISO/IEC 42001, EU AI Act and OECD AI Principles
Which framework, in what order, and with what evidence?
Four frameworks — and one question every board is asking: which one do we use? The honest answer is “it depends”. This course shows exactly what it depends on: how to choose the right combination for your organisation, sequence it across four implementation phases, and build governance that holds up under regulatory scrutiny and client due diligence.
It follows one running case: a fintech that discovers, mid-deal, that its credit-scoring engine is high-risk under the EU AI Act — and uses all four frameworks in sequence to close the gaps, achieve ISO/IEC 42001 certification and win the deal.
What you take away
- A practical method for selecting and sequencing frameworks for your context
- Templates with completed worked examples: AI risk register, gap-analysis scoring, EU AI Act obligations checklist, ethics-policy mapping and an implementation roadmap
- Practitioner-first content drawn from real regulatory engagements, not theory
Who it is for
Risk, compliance, legal and audit leaders; AI technical leads and architects; programme and project managers steering AI delivery.
View the course on Udemy ↗Live programmes for individuals and teams
Forward Deployed Engineer
Take enterprise AI from a client’s problem to a production system — and prove the value it delivers.
A 35-day pathway that first builds a complete AI engineer, then adds what makes a Forward Deployed Engineer: client discovery, rapid prototyping, enterprise integration, production operations and proving business value.
Explore the pathway →AI Engineer
From GenAI foundations to secure, production-ready agents in 20 days.
A beginner-to-advanced pathway covering LLMs, prompt engineering, RAG, evaluation, multimodal AI, fine-tuning, agents, MCP, LLMOps, security and governance — finished with a team capstone and demo day.
Explore the pathway →Compare the pathways
| Forward Deployed Engineer | AI Engineer | |
|---|---|---|
| Duration | 35 days | 20 days |
| Level | Beginner → Applied | Beginner → Advanced |
| Live sessions | 52.5 hours | 30 hours |
| Total learning | 167.5 hours | 90 hours |
| Capstone | 2 × 40-hour team projects | 1 × 40-hour team project |
| Who it is for | Software developers who want to move into Forward Deployed Engineer roles. No prior AI engineering experience is assumed: Stage 1 builds the foundation. | Junior software developers with some exposure to generative AI. No prior AI engineering experience is assumed. |
How every session runs
Concepts with real examples and a short live demonstration
Hands-on build that applies the day’s concepts
Practical, job-relevant task that extends the lab
2.5 hours of learning a day: one 90-minute live session plus homework. Each stage also includes a 40-hour team capstone completed outside the live sessions.
For individuals and for organisations
Join a cohort
Live, instructor-led cohorts with labs every session, practical homework and a team capstone you can show employers.
Enquire about the next cohortRun it for your team
A private cohort for your engineers, scheduled around your teams, with the capstone built on a use case from your own organisation.
Talk to us about a team cohort