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AI Advanced · Starts January 2027

AI Advanced — from builder to serious engineer.

Get in touch →All coursesFor students who finished Foundation and want to go further. Next cohort starts January 2027.
What’s different

Deeper, harder, mentored.

Advanced takes the depth out of Foundation and goes much further — real engineering, bigger projects, and direct mentoring.

Production machine learning

Train, evaluate and deploy real models — beyond no-code.

Multi-agent systems

Design systems where several AI agents plan and work together.

A bigger build, with incubation

A longer, more ambitious project, supported toward something real.

Mentored by an AI CTO

Guidance from an AI CTO of a top-tier organization.

for Foundation grads

Continue on from Foundation.

A deeper portfolio

Stronger evidence for top university and internship applications.

The course

What AI Advanced is.

The next step after Foundation — real engineering, a bigger build, and direct mentoring toward something you can actually ship.

ForFoundation graduates & capable older students ready to go deeper · some coding comfort expected
StartsJanuary 2027 · fully online, live cohorts
FormatLonger and project-led, in small mentored teams
MentoringDirectly mentored by an AI CTO of a top-tier organization
You buildA more ambitious, production-grade AI product, with incubation support
Ends inA deeper portfolio and an investor/peer-style pitch
What you’ll learn

From builder to serious engineer.

Three phases that take you from production fundamentals to shipping and pitching a real, more sophisticated AI product.

Part 1

Production-grade AI

Data & pipelines. Work with real data — cleaning, splitting and preparing it for models that hold up outside the classroom.
Training & evaluation. Train, evaluate and tune your own models; judge honestly whether a model is actually good.
Beyond no-code. Move into real code and APIs, integrating models into working software.
Engineering habits. Version control, testing and the discipline that separates a demo from a product.
Part 2

Advanced systems

Multi-agent systems. Design systems where several AI agents plan, delegate and work together toward a goal.
Retrieval at scale (RAG). Ground AI in your own knowledge properly — accurate, current and trustworthy.
Guardrails & evaluation. Add safety checks, human-in-the-loop and real evaluation so systems behave under pressure.
Deployment & MLOps. Ship to production, monitor it live and iterate based on real usage.
Part 3

Build, incubate & pitch

An ambitious build. A longer, more sophisticated project in a domain that matters, scoped with your mentor.
Incubation support. Ongoing guidance toward something real — users, feedback and iteration.
Responsible-AI review. Stress-test for bias, privacy and limits, and document the decisions you made.
The pitch. Present your innovation to investors and peers, and tell its story for top university and internship applications.
What you leave with

Outcomes & how to join.

A production-grade product

A deployed, more sophisticated AI product with real users — plus the engineering skills behind it.

A standout record

A deeper portfolio, a recorded demo and a verifiable achievement record — strong evidence for top universities and internships.

Mentored entry · for grads

Places are limited and mentor-led. Speak to a professional to check fit and reserve a place.

Speak to a professional →
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