Learn AI properly.
Free, for anyone, anywhere.
35 courses, 306 lessons, about 43 hours of real teaching — from what AI actually is, through designing, editing and building with it, to the maths underneath. No enrolment, no card, nothing behind a wall.
Start here
AI, Safety and What Goes Wrong
The failure modes of AI, stated plainly, with the numbers.
Getting Real Work Out of a Model
You already use ChatGPT, Claude or Gemini. This is how to stop getting average answers.
AI, Actually Explained
Nine short lessons for someone who was never told what this thing is.
Machine Learning, Foundations
The classical ground under modern AI, for someone who can read code.
How a Language Model Actually Works
The machinery under the chat box, explained without matrices.
Make things
Making Things With AI
Images, video, voice and music — how they work, where they break, who owns them.
Design, Before Any Software
Hierarchy, type, colour and spacing — the part of design you can do with a pencil, before any software.
Editing an Image
Layers, masks, curves and export — the craft behind a photo that still holds up at full size.
Vectors, Logos and Things That Get Printed
Draw curves that hold at any size, then hand a press a file it will not send back.
Image Generation, In Practice
Reference images, inpainting, character LoRAs, upscaling, and the licence nobody read.
Editing Video
Cuts, sound, colour and export — taught on DaVinci Resolve, which costs nothing.
Making It Say Something
Clean work that communicates nothing is the commonest self-taught failure, and it is fixable.
Hugging Face, End to End
Read a model card licence-first, run a Space for free, keep a token safe, publish something of your own.
Video With AI
Plan the shots, generate ten takes, throw eight away, and cut what is left in a real editor.
Motion, Sound and Music
Why nothing in the world starts at full speed, and why a blanket beats a better microphone.
Working For Yourself
Six portfolio pieces, twelve cold emails, a rate with arithmetic behind it, and a deposit before you start.
Use it in your work
AI at Work
The tasks it genuinely helps with, the ones it quietly ruins, and the line you must never cross.
AI for Teachers
For teachers who now have to teach and use AI, often with no training and no projector.
Working In AI
The roles that exist, what they pay, and how people get in without a famous degree.
Choosing and Using the Tools
A comparison written by someone selling none of them.
AI for a Small Business
Two or three tasks, honestly measured. Not a new department.
AI for Students
How to use these tools and still end up knowing things.
How Software Development Changed
Writing code got cheap. Knowing what to build did not.
Build with it
Python, From Zero, For AI
From your first line of code to your first API call.
Building Apps With AI
Build working software before you can write it, without fooling yourself.
Data, SQL and Getting to the Answer
Most AI problems turn out to be data problems. This is where you learn to ask a database a question and defend the answer.
Building With AI
From your first API call to a feature you can trust
Agents and Automation
What an agent actually is, and when you should build a script instead.
Shipping It
Get what you built in front of real people, and keep it alive.
Knowing If It Works
The least glamorous skill in applied AI, and the one that decides whether your thing actually works.
Context Engineering
The window is a budget. Learn to spend it.
Go underneath
The Maths You Actually Need
Eight ideas that carry almost all the weight in machine learning.
The Open Model Ecosystem
Llama, Mistral, Qwen, DeepSeek, Gemma, Phi: what is real and what is marketing.
Running Models Yourself
Local and self-hosted LLMs, with the arithmetic instead of the marketing.
Fine-Tuning, and When Not To
The case against fine-tuning first, then how to do it properly.
And two ways to get unstuck
The tutor explains
Ask anything, as many times as you need. It gives a hint, then a step, then the whole answer only if you ask twice — and for school subjects it follows your board's syllabus rather than a generic explanation.
Ask a questionThe study group refuses to
One question. You commit before you see anything else. Then four people who reason very differently argue about it — and some of them are wrong. You answer again. Only then does anyone tell you the answer.
Sit in on a roundEvery other AI tutor explains well.
That turns out to be the weaker half.
What the research says
Peer Instruction — commit privately, discover the room disagrees, argue, commit again — moves a class from roughly half correct to roughly four fifths. The lecturer's explanation is not the part doing the work. The argument between peers is.
Why nobody has shipped it
It needs a room full of people who genuinely disagree. A student alone at midnight has none, so every AI tutor falls back to explaining clearly — the half that was never the active ingredient.
What is different here
There is a room. The voices are chosen to disagree with each other as sharply as possible, and none of them is told which answer is right — so the wrong arguments are made honestly, and are worth beating.
And you cannot skip to the answer
Not because we ask you not to. It is not in your browser until you have decided twice — there is nothing there to extract.
And 4,860 questions, answered three ways
All 42 shelvesA researched overview, then the same question answered again by several people whose lives point in different directions, then open discussion. The disagreement is the content, not noise around it.
Free, with nothing behind a wall
No trial, no certificate upsell, no card at the end.
Nobody sees you struggling
Ask under a name nobody can trace. That is the point.
No scores on people
No ranks, no streaks, no leaderboard to fall off.
- No card
- No enrolment
- No certificate upsell
- No streaks
No ads. No data sale. No public scores on people. Ever.
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