Module 9 – Build Simple AI Projects! 🛠️
intermediate30 XP

Your First AI Showcase! 🚀

Use Google Teachable Machine to build and show off a real AI project — no code needed

Your First AI Showcase! 🚀

You've Learned So Much — Now Show It Off!

Time to build something impressive to show your friends and family. We'll use Google Teachable Machine to create a real AI project.

🎯 Project Ideas (Pick One!)

Idea 1: The Mood Detector 😊😢😠

Train AI to recognise 3 facial expressions:

  • Happy face → plays happy music
  • Sad face → sends an encouraging message
  • Surprised face → shows a funny GIF

Steps:

  1. Go to teachablemachine.withgoogle.com
  2. Choose "Image Project" → "Standard image model"
  3. Create 3 classes: Happy, Sad, Surprised
  4. Take 50+ photos of each expression (use webcam!)
  5. Click "Train Model"
  6. Test it — does it read YOUR mood?

Idea 2: Rock Paper Scissors AI ✊✋✌️

Train AI to recognise hand gestures:

  • Fist = Rock
  • Flat hand = Paper
  • Two fingers = Scissors

The AI plays against you in real time!

Idea 3: The Homework Helper Detector 📚

Train AI to detect:

  • "Working hard" (sitting at desk with book)
  • "Distracted" (phone in hand 😅)
  • "Taking a break" (stretching, standing)

Idea 4: The Sound Detector 🔊

Use the Audio project:

  • Train it to recognise: a clap, a snap, "hey computer"
  • Use this to trigger different actions!

📋 Your Project Checklist

□ Chose a project idea □ Created 2-3 categories in Teachable Machine □ Collected 50+ examples per category □ Trained the model (watched accuracy improve!) □ Tested with NEW examples it hasn't seen □ Shared with someone and showed them how it works! □ BONUS: Export and embed in a website or Scratch project

🏆 Level Up: Connect to Scratch!

Teachable Machine works with Scratch! You can:

  1. Export your model
  2. Import it into Scratch using the Teachable Machine Scratch extension
  3. Make sprites react to your AI predictions
  4. Build a full interactive game powered by YOUR AI!

💡 What Real AI Engineers Do

Congratulations — you've just done EVERYTHING a real AI engineer does:

  1. ✅ Defined the problem (what should AI detect?)
  2. ✅ Collected training data (photos/sounds)
  3. ✅ Trained the model
  4. ✅ Evaluated performance (accuracy)
  5. ✅ Deployed it (shared/used it)
  6. ✅ Iterated (improved by adding more data)

You are officially an AI builder! 🤖🔨

Quick check

01/2

What does Teachable Machine's 'accuracy' percentage tell you?