01
A model that predicts from real-world data
Train, test, and read the score. They can explain what the model is guessing and where it fails.
Teen & Pro track
AI & Machine Learning
Not prompt tricks — actual understanding. How models learn, where they fail, and how to build and evaluate one yourself.
Ages 14–18
16 weeks
Advanced
Live online
Understand the thing everyone is talking about.
What they'll walk away with
- Explain how a model learns from data, in plain language
- Prepare and explore a dataset properly
- Train, test, and evaluate real models
- Think critically about bias, limits, and responsible use
Curriculum
4 modules over 16 weeks, each ending in something built.
01
Data first
- What data actually is
- Cleaning and exploring datasets
- Visualising to find patterns
02
How models learn
- Prediction and classification
- Training, testing, and overfitting
- Measuring whether a model is any good
03
Building
- Your first trained model
- Neural networks, demystified
- Working with text and images
04
Responsibility
- Bias and fairness in data
- Limits and failure modes
- Capstone: build and defend a model
Skills covered
Python
Data Analysis
Machine Learning
AI Ethics
What you'll need
- Solid Python fundamentals required
- Comfort with basic algebra
- A computer with internet
Projects they'll build
Every module ends in something they can run, show, and keep. These are the pieces that leave the class with them.
02
An image classifier
A model that looks at pictures and labels them — the first time AI feels like something they built, not a chatbot.
03
A written analysis of a model's limits
Bias, overfitting, and a honest write-up. The project is the thinking, not just the accuracy number.
Keep going
Other courses on this track
Most learners move through two or three courses as they grow.
Try AI & Machine Learning for free.
One live demo class, no commitment. See if it clicks before you decide anything.