Junior AI Explorers

1. Week 1Teach a computer to tell fish from rubbish.

   Mission: Save the Ocean!

   Children meet machine learning by training an educational model to sort sea creatures from rubbish — then discover what happens when its examples aren't good enough.

   Using Code.org's AI for Oceans learning activity, explorers label examples and watch an educational model learn to recognise fish and rubbish.

   We compare learning from examples with following fixed instructions, and look closely at the mistakes the model makes — and why.

   Learning outcomes

   • Discover what AI is (and isn't)
   • Understand classification
   • Recognise that AI makes mistakes
   • Practise critical thinking

   Tools & approach

   Code.org AI for Oceans (no child accounts required)

2. Week 2More examples, better guesses?

   Mission: Train Your Own AI Robot

   Explorers experiment with object recognition in an instructor-supervised demonstration, testing how the number and variety of training examples changes what the model gets right.

   The instructor runs an object-recognition model — Google Teachable Machine is one potential tool, subject to its current terms and our age-appropriate operating arrangements.

   We train with everyday objects and prepared examples — never children's faces or voices — then challenge the model with tricky new items.

   Learning outcomes

   • Explain what training data is
   • See how variety in examples affects accuracy
   • Design fair tests
   • Spot bias in a data set

   Tools & approach

   Instructor-operated image model, using objects only

3. Week 3Code a performance with rhythm and style.

   Mission: AI Dance Party

   Children choreograph a digital dance performance using an age-appropriate Code.org activity, learning that sequences, patterns and instructions are the building blocks of every program.

   Explorers build dance routines from blocks, use loops and events to react to the music, and add their own creative flair.

   We talk about where AI can help creative work — and where human imagination is still in charge.

   Learning outcomes

   • Build sequences and patterns
   • Use loops and events
   • Debug a routine
   • Express creativity with code

   Tools & approach

   Code.org Dance Party-style block coding

4. Week 4Invent a creature, character or world.

   Mission: AI Imagination Lab

   Using picture-based prompt cards, children design a fictional creature or world. The instructor operates any generative AI tool, and children review the results critically before creating their own poster or comic.

   Children never use a chatbot or image generator themselves. They choose describing words from visual prompt cards; the instructor types the fictional prompt.

   No names, photos or personal information are ever entered. Explorers judge the output: what did the AI get right, what did it invent, and how would they improve it?

   Learning outcomes

   • Describe ideas precisely
   • Evaluate AI-generated content critically
   • Understand that AI can be wrong or biased
   • Turn ideas into an original poster or comic

   Tools & approach

   Instructor-operated generative AI, fictional prompts only

5. Week 5Build a playable game from scratch.

   Mission: Become a Game Inventor

   Explorers make a playable game in Scratch with movement, obstacles, scoring and interactions — then compare traditional programming with the AI they have explored so far.

   Scratch is a visual programming language, not an AI tool: children write the rules themselves. That makes it a perfect contrast with week one's learning-from-examples approach.

   Every explorer leaves with a working game and a clearer sense of the difference between coding and AI.

   Learning outcomes

   • Program movement and collisions
   • Use variables for scoring
   • Test and improve a design
   • Compare rules-based code with machine learning

   Tools & approach

   Scratch (offline editor, no child accounts required)

6. Week 6Show, tell and celebrate.

   Mission: The AI Inventors Expo

   Children choose their favourite projects and prepare a mini exhibition, explaining what they made, what they learned and how to use AI responsibly.

   Explorers practise presenting their work, give each other kind and useful feedback, and reflect on their six missions.

   The course ends with certificates and — where suitable arrangements allow — a short showcase for parents and carers.

   Learning outcomes

   • Present and explain a project
   • Reflect on learning
   • Share responsible-AI rules of thumb
   • Celebrate achievements

   Tools & approach

   Children's own projects from weeks 1–5

Code.org, AI for Oceans, Google Teachable Machine and Scratch are trademarks of their respective owners. AI Explorers Academy is independent and not affiliated with or endorsed by them. Tools may change if their terms or suitability change.