Every kid will use AI. Yours will understand it.
Students train and test real machine learning models: image classifiers, language tools, game-playing agents. They learn to reason about where AI succeeds, where it fails, and why, by building with it every week.
Small groups, one mentor, every week
Group size
The smallest ratio on the floor. AI work is discussion-heavy, so groups stay tight.
Minutes weekly
One bench session per week, same mentor, same cohort, all term.
Ages
Starts at 10; the program assumes typing and basic logic, not prior AI knowledge.
WWCC mentors
Every mentor holds a Working with Children Check and teaches, not minds.
From first trained model to an AI-powered app of their own.
Meet the models
Train an image classifier live and watch what it gets right and wrong. Learn what training data actually does.
Direct the machine
Prompting, evaluating and correcting AI output. Compare model answers against their own thinking.
Call it from code
Use Python to call AI APIs: build tools that generate, classify and answer, with the student in control.
Ship an AI app
Capstone build: a working app with an AI feature at its core, documented and demoed at showcase night.
Projects from the Applied AI benches
Image classifier
Voice command bot
Trained game-playing agent
Custom chatbot
Group ratio 1:6, 90 min weekly sessions. Every term ends with a showcase night where students demo their build to family and peers.