← AI AcademyFive stages · English

From curiosity to creation

Explore the AI Learning Map.

Start by spotting everyday patterns. Grow into testing predictions, building programs and understanding modern AI. Every stage has a small activity to try.

80/20 core ideasHands-on practiceFamily-friendly startFuture goals clearly labeled

The 80/20 ideas

Five things every learner revisits.

Start with simple examples and add deeper mathematics and programming at later stages.

  1. SensingComputers receive information from data and sensors.
  2. PatternsSome AI systems learn patterns from examples.
  3. RepresentationsMachines use numbers and rules to process information.
  4. PredictionsModels classify, predict and generate outputs.
  5. ResponsibilityPeople must test AI and consider fairness and privacy.

Advanced concepts for older learners

The new AI Foundations & Engineering pilot offers 11 original, detailed concept lessons on language models, transformers, tools, fine-tuning and safety. This is review-stage supplementary reading, not a complete AI Engineers course.

Choose a learning stage

From playful questions to engineering.

Select one stage or show the full journey. The filter does not save learning data or assess progress.

Showing all five stages.

01 · Ages 3–5

Little Explorers

Find patterns, sort objects and practise clear instructions.

Future

Explore and practise

  • Sort objects by color and shape
  • Give a person simple robot commands
  • Notice when a rule changes

Build or imagine

Make a paper garden with three sorting rules.

Explain it back

Can the child explain the sorting rule?

Care and safety: Offline play with an adult is enough.

Planned pathway, no course released yet
02 · Ages 7–9

AI Discoverers

Explore AI with stories, predictions, errors and thoughtful decisions.

Family beta · 8 lessons

Explore and practise

  • Compare a fixed robot rule with learned patterns
  • Try varied apple and banana examples
  • Check a believable but incorrect AI answer

Build or imagine

Design a helpful garden robot on paper.

Explain it back

Can the learner explain why AI can be wrong?

03 · Grades 4–6

AI Detectives

Learn to collect examples and test whether predictions are reliable.

Future course · vocabulary pilot available

Explore and practise

  • Create a labeled paper dataset
  • Test with unseen examples
  • Count the model's mistakes

Build or imagine

Design a paper-based fruit classifier and mistake log.

Explain it back

Can the learner explain the difference between training and testing?

04 · Grades 7–9

AI Creators

Build small programs and explore useful machine learning.

Future course · agent lab pilot available

Explore and practise

  • Learn variables and Python basics
  • Compare rules against learned models
  • Measure accuracy on new test items

Build or imagine

Prototype a plant classifier using synthetic data.

Explain it back

Can the learner explain a prediction error and improve a test?

Care and safety: Check third-party age, account and privacy requirements with an adult.

Planned pathway, no course released yetTry the safe agent pilot
05 · Grades 10–12

AI Engineers

Explore the mathematics and engineering of modern AI.

Future

Explore and practise

  • Model vectors, functions and probabilities
  • Understand neural networks and token attention
  • Evaluate reliability, bias and model limitations

Build or imagine

Build a small text classifier and document failure cases.

Explain it back

Can the learner explain why training accuracy alone is insufficient?

Care and safety: Use properly licensed or synthetic data and human review.

Planned pathway, no course released yet

Optional resources

Explore trusted starting points.

These external tools and websites are optional. A parent or educator should first review age limits, accounts, safety, privacy, costs and suitability. Never upload a child's face, voice or personal details for these activities.

AI education framework

AI4K12

Five big ideas for learning AI.

Visit resource
Teacher resources

MIT Day of AI

Explore teacher-guided activity materials.

Visit resource
Visual programming

Scratch

Create simple interactive programs and stories.

Visit resource
Model experiment

Google Teachable Machine

Train simple models with non-personal examples and adult oversight.

Visit resource
Senior coding reference

Python Tutorial

Learn the Python language with practical examples.

Visit resource
Responsible AI literacy

UNESCO AI Competency Framework

Explore human agency, ethics and creating with AI.

Visit resource

Family challenge

Teach with paper, fruit and curiosity.

Draw three red apples and three yellow bananas. Make a rule that distinguishes them. Now introduce a green apple. Will the rule still work? Discuss how varied examples and careful testing make a system more useful.

Where to begin

The eight AI Discoverers lessons are available as a Family beta. All other stages are future curriculum plans, not finished courses.

Explore the lessons