AI is the most powerful car you've never been taught to drive. This is driving school.
You define the problem. You set the direction. You decide what good looks like and check the work against it. AI does the execution. Work through real projects for fictional clients across seven areas of tech.
Give AI the right context, direct it through real workflows, audit what it produces against what you asked for, and know when to push back. This is the curriculum.
- 01Web DevelopmentBuild sites and apps, from static pages to full-stack deployments.— Start here if you want to see things come to life in a browser.24 projects→Build sites and apps, from static pages to full-stack deployments.— Start here if you want to see things come to life in a browser.
- 02Machine LearningTrain models and build LLM applications, from prototypes to production.26 projects→Train models and build LLM applications, from prototypes to production.
- 03Cloud EngineeringInfrastructure, IaC, and deployment pipelines from provisioning to observability.26 projects→Infrastructure, IaC, and deployment pipelines from provisioning to observability.
- 04CybersecurityAttack systems, detect the breach, and build the defenses.24 projects→Attack systems, detect the breach, and build the defenses.
- 05Analytics & BIDefine metrics, build dashboards, and make sense of experiments.— Most accessible entry point for data.23 projects→Define metrics, build dashboards, and make sense of experiments.— Most accessible entry point for data.
- 06Data EngineeringBuild the pipelines and quality systems that data depends on.— How data moves, not just what it says.24 projects→Build the pipelines and quality systems that data depends on.— How data moves, not just what it says.
- 07Data ScienceExplore data, build models, and turn findings into recommendations.— Heavier on statistics and modelling.18 projects→Explore data, build models, and turn findings into recommendations.— Heavier on statistics and modelling.
Every discipline has a real-world professional loop. The platform follows that loop from day one — the same path practitioners walk every day. What changes across projects isn't the loop. It's the terrain.
You never build by hand. You learn to direct AI through the loop — what to ask for, what inputs it needs, what good looks like, and how to check you got it. By the end, you will have done that on real projects, start to finish, and checked the results yourself.
You're OK with computers and want a lot more: to pivot into tech, to cross from the IT work you do into a neighbouring discipline, or to learn to judge, scope and explain work you can already type. Plenty of courses teach AI to people who find computers hard. This one starts where those stop. It assumes you can install software, work in a terminal and judge a result, and uses AI to take you from there through the professional loop of seven disciplines.