Getting Started with AI
Ten short modules, then a build project for your portfolio. No jargon, no hype — just what actually works.
Cut through the noise: what today's AI tools genuinely do, what they cannot do, and why the difference matters for your work.
5 min read
Tokens, training, context windows and sampling: just enough of the machinery to explain the strange behaviour you will run into.
8 min read
The four ingredients that separate a prompt which produces generic filler from one that produces something you would actually send.
6 min read
Why pasting in your own material transforms results, how to give a model what it needs without oversharing, and what "training it on my data" really means.
8 min read
Why AI invents facts with total confidence, which situations make it most likely, a checking routine that takes under a minute, and how grounding changes the odds.
8 min read
The people who get the most from AI rarely accept the first answer. Here is how the back-and-forth actually works.
5 min read
A practical map of tasks worth delegating, tasks to keep, and the ones that look like wins but cost you later.
6 min read
Where your data actually goes, what data protection law means for you in practice, and a rule you can apply in two seconds.
6 min read
Chat tools, reasoning models, search-connected assistants and document tools: what the categories are, when each one matters, and what the product wrapped around the model is doing.
7 min read
Most people try AI, find it interesting, and quietly stop. Here is how to turn what you have learned into something that sticks.
5 min read
Build the file module 10 told you to keep: three tested prompts for your recurring weekly work, a standing context block above them, and a verification line under each.
75 min to build
AI courses for your profession
An AI course built around the real tasks of your job — for teachers, coders, nurses, business owners, and more. Each one ends with a build project and a certificate.
See what's inside