AI learning paths

Structured paths to go from where you are to working in AI — each one built around real projects, not a reading list.

AllBuild AI systemsApply AI to your jobLead AI in your companyFoundations & research
4 paths

Machine Learning

Foundations & researchPython & pandas for real dataExploratory analysis that finds bugs
Machine Learning

From a messy table to a model you can defend in a meeting.

Intermediate → Advanced · Duration: 6-9 months

Deep Learning

Foundations & researchTensors, shapes and autogradBackpropagation from first principles
Deep Learning

Understand neural networks well enough to debug them at 2am.

Advanced · Duration: 8-12 months

NLP & Transformers

Foundations & researchTokenisation and subword algorithmsMorphology-aware preprocessing for Arabic
NLP & Transformers

Understand how machines read language — and why they read Arabic badly.

Intermediate → Advanced · Duration: 6-9 months

Computer Vision

Foundations & researchImage fundamentals & colour spacesDataset building and annotation quality
Computer Vision

From pixels to a camera that works in a real, badly lit room.

Advanced · Duration: 6-9 months

How to use these paths

  1. Pick the path that matches where you want to end up, not the one that sounds most impressive.

  2. Follow the phases in order — each one assumes the previous.

  3. Build every project. A path you only read is a path you did not do.

  4. Expect the timings to slip. They assume steady weekly effort, not a sprint.

Want to walk one of these paths with a coach and a cohort?

Discover the 212AY Academy →