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Code Creators: Scratch & AI Lab

AI course

Code Creators: Scratch & AI Lab

Members train their own AI to recognize hand signs, then build a Scratch-style game their AI controls — across ten guided stages.

Final project previewAI Collector Game
AI Collector Game mockup with hand-sign prediction, score, timer, and falling objects
10playable stages
16 weekssemester or 5-day intensive
2 toolsTeachable Machine + RAISE

What members ship

A real AI game, trained and built by the member

Every stage adds one piece of the same project. By the last stage members have an AI model they trained from scratch and a game their AI controls — plus a short demo they can show at the showcase.

An AI model you trained on your own examples

A Scratch-style game your AI controls

A polished demo you can show at the showcase

Project moments

Each stage adds something members can see and play

Every stage produces a visible change you can run, test, and tweak — the screen is the proof.

Four labeled photo groups for Rock, Paper, Scissors, and Nothing feeding into a Train Model button

An AI you trained yourself

Members take photos of rock, paper, scissors, and “nothing,” then watch the AI start to recognize them. It is the moment training stops feeling like magic.

A webcam hand sign and confidence bars showing Rock as the strongest AI prediction

The AI guesses live

Confidence bars climb and fall as the member changes their hand. Stage 3 turns those bars into the lesson: an AI is never “sure,” it is just sure enough.

Scratch-style blocks using an AI prediction to move a sprite on a game stage

Hand sign moves the sprite

The AI prediction becomes a control. Show a sign, the sprite reacts. This is where the project goes from “cool demo” to “real game.”

AI Collector Game stage with a player catching stars, score readout, and timer

Score climbs in the Collector Game

Falling objects, a score counter, a goal. The same pattern members see in every arcade game — powered by an AI they built themselves.

Course path

Your project grows stage by stage

Each stage names what is new in the project and the one idea behind it.

Stage 1

AI Learns from Examples

Stage 2

Train Your First Model

Stage 3

Test and Improve Your Model

Stage 4

Connect to RAISE Playground

Stage 5

Show the AI Prediction

Stage 6

Control a Sprite with AI

Stage 7

Build the Game Rules

Stage 8

Customize the Game

Stage 9

Final Build and Demo Practice

Stage 10

Final Demo Showcase

How to start

  1. Ask your instructor for your class code. They read it out at the start of class.
  2. Make your account. First name, last name, a username and a password you pick.
  3. Sign in anywhere. Your work is saved to your account, not to one computer.

For instructors

Pacing labs are required

Each stage now includes timed testing, journaling, partner checks, or rehearsal work before stretches. Use those labs to keep the room together and fill the 3-hour block.

Open the Instructor Guide

What is AI?​

AI stands for artificial intelligence. That is just a long way to say a computer that learns from examples.

The computer does not start out knowing what rock, paper, or scissors look like. We show it pictures. We tell it the name of each picture. We let it practice. After enough practice, it can guess what it sees on its own.

That is the whole secret. The rest of this course is just doing that — and then building a game with the AI we trained.

How the two tools connect​

Teachable Machine and RAISE Playground are two parts of one project.

Teachable Machine is where the AI learns from photos. RAISE Playground is where the game asks that trained AI what it sees. The model URL is the link between them.

How the two tools connect
Photosexamples in Teachable Machine
Modelthe AI after training
Model URLthe address of the AI
RAISEloads the model
PredictionRock, Paper, Scissors, Nothing
Game actionsay, move, score, win

Teachable Machine trains the AI. RAISE Playground loads that trained AI and uses its predictions inside the game.

Course time​

Course Intro (30) · Course Setup (45) · Stage 1 (45) · Stage 2 (60) · Stages 3–8 (90 each) · Stage 9 (120) · Stage 10 — Final Demo (60) = 900 minutes, about 15 hours.

The course closes with a showcase. Plan around it.

Stages also include required Pacing Labs. These are not optional stretch challenges. They are timed testing, journaling, peer-review, and rehearsal blocks that keep the room together and fill out a long session.

That same material runs two ways:

  • School semester — one class a week for 16 weeks. One stage per week, with catch-up, stretch, and showcase weeks built in.
  • 5-day intensive — 3 hours a day for 5 days. Two to three stages a day, closing with a showcase.

Instructors: the week map and the day-by-day plans are both in the Instructor Guide.

For instructors — duration check

If a stage runs long, pull time from stretch challenges first. Keep the Pacing Labs whenever possible — they are the built-in slow-down work that turns quick builds into a full session. Stage 10 (the demo) is the only block that should never get squeezed.

Who this is for​

This course is built for beginners. Reading levels and language stay simple. New words get defined in a vocab card every time they appear. Every stage has a short "Instructor demo" callout at the top and an "Instructor notes" callout at the bottom — instructors can scan those two callouts to know what to show and what to watch for.

Members do not need to know how to code beforehand. They will use two tools:

  • Teachable Machine to train the AI.
  • RAISE Playground to build the Scratch-style game.

Both run in the browser. No installs.