AI — Grade 6
A hands-on introduction to AI mapped to the ICSE syllabus — what AI is and where it already shows up, how it learns from data, how a model is built, trained and tested, what AI can and cannot do, and bias, fairness and safe use.
Don't just read about or use AI. Build, train, test, and make models fair.
Discover how intelligent systems learn, make predictions, make mistakes, and change with experience.
No coding required · Learn by doing · Built from first principles
You see faces and label them happy or sad. That is all the teaching it gets.
Press Train. Nobody tells it about smiles or frowns. It finds what matters by itself.
Now faces it has never seen. What does it say?
It never learned the smile. It learned the colour. Blue means sad. Yellow means happy.
Add the missing faces. Train again.
Every course maps to the board syllabus and is aligned with NEP 2023. These are summaries — the full lesson list for each one is on the courses page.
AI curriculum that grows with students — with age-appropriate concepts, activities and increasing depth.
A hands-on introduction to AI mapped to the ICSE syllabus — what AI is and where it already shows up, how it learns from data, how a model is built, trained and tested, what AI can and cannot do, and bias, fairness and safe use.
Builds on Grade 6. How AI sees, hears and reads — images, sound and language as data — the full cycle of building a model, checking how well it performs, and thinking through the ethics of using AI responsibly at school and beyond.
A first look at AI for middle school — everyday examples, the data behind them, spotting patterns and deciding from them, and the digital-responsibility habits that come with it.
Builds on Grade 6. The domains of AI and the techniques behind them, how AI is used across healthcare, transport, agriculture and education, reading and analysing real data, and the named types of bias.
Builds on Grade 7. Machine learning in more depth — supervised and unsupervised learning, training and evaluating models on real datasets, an intuitive look at neural networks, and AI’s impact on society and the world of work.
Our open course for anyone starting out, with no grade attached. Machines learning from numbers, then from images, then from sound — each one a hands-on activity you run yourself.
Four principles shape every lesson.
Games first. Drop houses on the map, let an untrained AI open three pizza shops wherever it likes, then train it and watch the shops move to where people live. Play it right here.
More games in the playground →How does a machine learn from data and predict? Students learn it from the ground up: the machine finds a mathematical pattern in the data, represents it as a formula, and uses the formula to predict new values.
Students learn by doing — drawing, labelling, training and testing. Every lesson is hands-on.
A confident answer is not always the right one. Students check what the AI was shown, weigh what it missed, and decide for themselves. Try it.
What would you do?
What the AI saw
It wasn’t wrong. It was blind. It decides from the data it is given. You can see more than it can.
Search, recommendations, maps, games, chatbots, images and music. AI is making predictions around you every day. Understanding how it works helps you question it, use it and build with it more intelligently.
Start with a challenge, not a definition. Make a choice, answer a question, and then discover the concept.
Any way you like. Click a number to send it to group A, click again for group B.
How did you decide?
You had no instructions. You looked at the numbers, found a pattern, and grouped them. That is the basic idea behind unsupervised learning. In unsupervised learning, the AI gets data without labels or group names. It looks for patterns and groups things that are similar.
Photos and first names. That is all you get.
How did you decide?
Now the facts.
Build the habit of asking “Why?”
AI literacy is not just knowing vocabulary. It is understanding what is happening underneath and thinking carefully about the result.
Start with simple foundations and build up, so understanding replaces memorising terms.
Question AI outputs. Ask what happened, why it happened and what data shaped it.
Move from “AI feels like magic” to “I understand what's happening underneath.”
Explore trial lessons and the AI Playground. Train, test, experiment and see how AI learns.
Soccer Free Kick · Open Pizza Shops · Lego Price Prediction — all three free, no account.