The AI Playroom | AI Education for Kids in Singapore
Complete Curriculum Guide

AI Creators Curriculum

A hands-on, project-driven program where students build real AI-powered tools using intuitive, age-appropriate platforms, exploring concepts like image classification, chatbots, model training, and ethical AI.

7-12
Age Range
8
Levels
10-12
Weeks/Level
26
Topics
Progressive Learning
Hands-on Projects
Expert Instruction

Learning Outcomes

  • How AI systems are trained using data
  • The difference between programming and machine learning
  • How to build tools like image classifiers, voice assistants, and recommendation systems
  • Why AI can be biased—and how to design fairer systems
  • How to explain AI decisions in human-friendly terms
  • Basic programming concepts such as logic, sequencing, input/output, and conditions

Our AI Approach

AI Creators doesn't just use AI—students understand how it works, how to improve it, and how to use it responsibly. The first two levels include integrated coding support to help beginners build a strong foundation in logic and interaction design.

Learning Journey

8
Total Levels
1-3

Foundation Building

Master core concepts, basic logic, and fundamental programming principles

4-6

Skill Development

Apply knowledge to complex projects, explore AI concepts, and build interactive systems

7-8

Advanced Application

Create sophisticated projects, understand ethics, and showcase mastery through capstone work

Who This Program Is For

Students typically join AI Creators around age 9+, either after completing Code Explorers Level 6–8 or as a fresh start with strong interest in real AI tools. Optional onboarding tutorials and jumpstart sessions are available for new learners.

Program Completion Outcomes

By the end of AI Creators, students will understand how AI works, know how to design and train simple models, use AI tools creatively and responsibly, and build and present their own intelligent system.

Complete 8-Level Curriculum

Each level builds upon the previous one, creating a comprehensive learning journey that develops both technical skills and creative thinking. Students progress at their own pace while mastering essential concepts.

1

Thinking Like AI

Coding logic + understanding AI vs. traditional programming
10-12 weeks

Students learn fundamental coding concepts while exploring what makes AI different from traditional rule-based programming, using visual tools and platforms like Teachable Machine.

Sample Project Outcome

An image classifier that distinguishes pets (e.g., cat vs dog), connected to a visual output or animation in a game interface.

Core Topics (4)

Learning Outcomes
  • Create event-driven programs
  • Understand program flow and sequencing
  • Design responsive user interfaces
Learning Outcomes
  • Write conditional statements
  • Create trigger-based interactions
  • Design decision-making systems
Learning Outcomes
  • Distinguish between AI and traditional programming
  • Understand machine learning concepts
  • Recognize AI applications in daily life

Skills Developed in This Level

Event-driven Thinking and Sequencing
Simple Conditions and Triggers
AI vs Traditional Programming
Introduction to AI with Teachable Machine
2

Training AI with Data

How models learn from examples, dataset quality, accuracy
10-12 weeks

Students learn how AI models learn from data, exploring dataset quality, training processes, and how to evaluate and improve model performance.

Sample Project Outcome

A custom classifier trained to recognize hand gestures or moods, with programmed reactions built into a game or story app.

Core Topics (4)

Learning Outcomes
  • Create balanced datasets
  • Understand data labeling principles
  • Recognize data quality issues
Learning Outcomes
  • Understand train/test data splits
  • Evaluate model performance
  • Prevent overfitting in models
Learning Outcomes
  • Connect AI outputs to program logic
  • Create responsive AI-driven interfaces
  • Handle prediction uncertainty

Skills Developed in This Level

Collecting and Labeling Data
Training and Testing Sets
Coding Logic for Predictions
Accuracy and Model Refinement
3

Using AI in Projects

Embedding AI into games, apps, or real-world tools
10-12 weeks

Students learn to integrate AI models into interactive projects, creating games and applications that respond intelligently to user input.

Sample Project Outcome

A game where webcam input from a trained model determines story branching or difficulty level.

Core Topics (3)

Learning Outcomes
  • Map AI predictions to actions
  • Create AI-driven game mechanics
  • Design intelligent user experiences
Learning Outcomes
  • Build real-time AI interactions
  • Create responsive AI applications
  • Design user-friendly AI interfaces
Learning Outcomes
  • Connect AI models to visual programs
  • Create data-driven animations
  • Build interactive AI demonstrations

Skills Developed in This Level

Connecting AI Outputs to Decisions
Building Interactive AI Systems
Visual Coding Integration
4

Fairness and Bias in AI

Ethics, dataset bias, testing for fairness
10-12 weeks

Students explore critical questions about fairness and bias in AI systems, learning to identify problems and design more inclusive AI solutions.

Sample Project Outcome

A classifier that initially performs unfairly, followed by student-led redesign with more balanced data.

Core Topics (3)

Learning Outcomes
  • Identify bias in training data
  • Understand data representation issues
  • Recognize model behavior patterns
Learning Outcomes
  • Detect unfair AI outcomes
  • Analyze bias in AI systems
  • Understand societal impact of AI bias
Learning Outcomes
  • Create more balanced datasets
  • Design inclusive AI systems
  • Test for fairness across groups

Skills Developed in This Level

How Training Data Shapes Behavior
Identifying and Reflecting on Bias
Improving Inclusiveness and Equity
5

Natural Language and Chatbots

Basic NLP and chatbot design using pre-trained tools
10-12 weeks

Students explore natural language processing and create their own chatbots, learning how AI can understand and generate human language.

Sample Project Outcome

A chatbot that role-plays a character or guides a user through a choose-your-own-adventure game.

Core Topics (3)

Learning Outcomes
  • Understand natural language processing basics
  • Design conversation flows
  • Handle user input variations
Learning Outcomes
  • Design conversation trees
  • Manage conversation context
  • Create engaging dialogue systems
Learning Outcomes
  • Use pre-trained NLP models
  • Create helpful AI assistants
  • Design natural interactions

Skills Developed in This Level

How Chatbots Interpret Input
Designing Multi-turn Conversations
Applying NLP Tools
6

Recommendation and Personalization

Building systems that respond based on user behavior
10-12 weeks

Students create recommendation systems that learn from user preferences and behavior to provide personalized experiences.

Sample Project Outcome

A simple recommender tool that offers suggestions (e.g., music, books, or emojis) based on user responses.

Core Topics (3)

Learning Outcomes
  • Design preference collection systems
  • Store and manage user data
  • Respect user privacy
Learning Outcomes
  • Create recommendation algorithms
  • Understand collaborative filtering
  • Design personalized experiences
Learning Outcomes
  • Analyze user behavior patterns
  • Create adaptive content systems
  • Balance personalization and privacy

Skills Developed in This Level

Collecting User Choices and Preferences
Simulating Recommendation Systems
Tracking User Patterns
7

AI in the Physical World

Using AI alongside sensors or hardware (optional robotics integration)
10-12 weeks

Students explore how AI can interact with the physical world through sensors and hardware, creating intelligent physical systems.

Sample Project Outcome

A robot that reacts to user gestures or voice commands using AI-based classification.

Core Topics (3)

Learning Outcomes
  • Integrate AI with sensor data
  • Create responsive physical systems
  • Understand edge AI concepts
Learning Outcomes
  • Connect AI decisions to physical outputs
  • Create intelligent automation
  • Design safe AI-controlled systems
Learning Outcomes
  • Build AI-controlled robots
  • Create intelligent robotic behaviors
  • Understand embodied AI concepts

Skills Developed in This Level

Connecting AI to Real-world Sensors
AI Triggering Physical Actions
Optional LEGO SPIKE AI Projects
8

Capstone AI Challenge

Design, build, test, and present a complete AI system
10-12 weeks

Students design and build their own complete AI system, integrating everything they've learned while considering real-world impact and ethical implications.

Sample Project Outcome

A final showcase project such as an AI-based game, voice assistant, or recommendation engine—complete with student presentation and ethical reflection.

Core Topics (3)

Learning Outcomes
  • Design comprehensive AI projects
  • Create project timelines and milestones
  • Prototype and iterate on ideas
Learning Outcomes
  • Create user-friendly AI interfaces
  • Integrate ethical considerations
  • Balance functionality and responsibility
Learning Outcomes
  • Analyze potential AI impacts
  • Consider ethical implications
  • Present responsible AI solutions

Skills Developed in This Level

Planning and Prototyping AI Projects
Integrating AI Logic, Interface, and Ethics
Real-world Impact and Responsibility

Ready to Start Your Child's AI Journey?

Join AI Creators and give your child the skills they need for the future. Our expert instructors and proven curriculum make learning AI fun, accessible, and impactful.

Expert Instructors
Small Class Sizes
Proven Curriculum
Real Projects