📚 FutureTec Academic Syllabus
A comprehensive 12-month "Unplugged AI" curriculum designed to build the logical minds of tomorrow.
Our program follows international K-12 Computer Science Frameworks and UNESCO AI Ethics principles.
🧒 Ages 5–6: Little Explorers
A gentle introduction to the world of patterns, sequences, and logic through play.
Month 1: The Clapping Code
Learning patterns through rhythm. Children clap sequences (Clap-Clap-Stomp) and match them with colorful wooden blocks. AI Concept: Pattern Recognition.
Month 2: Robot Sandwich Maker
Children give step-by-step instructions to a "Robot" (the teacher). If they forget a step, the robot fails! AI Concept: Algorithms must be precise.
Month 3: Fruit or Veggie?
Sorting 3D blocks by texture and color. Children learn to group objects by features. AI Concept: Classification.
Month 4: The Treasure Map
Following a simple step-by-step map to find hidden "treasure." AI Concept: Sequential instructions.
Month 5: Copy Cat
One child builds a pattern, the other copies it without seeing. Communication through instructions only. AI Concept: Data transfer.
Month 6: The Sorting Race
Racing to sort objects by size, color, and shape. Which method is fastest? AI Concept: Efficiency & optimization.
Month 7: Yes or No Garden
Walking through a physical "garden" answering Yes/No questions to find the right flower. AI Concept: Simple decision trees.
Month 8: The Memory Game
Matching pairs of cards. How does remembering help us find answers faster? AI Concept: Data storage & retrieval.
Month 9: My First Network
Passing colored balls through a chain of friends. Each friend adds a color. AI Concept: Simple neural network simulation.
Month 10: The Fairness Game
Playing a game with "unfair" rules. Children spot what's wrong and fix it. AI Concept: Algorithmic bias (simplified).
Month 11: Robots Are Our Friends
Drawing "helper robots" for the community. What should robots do? What should they never do? AI Concept: AI ethics.
Month 12: My AI Invention
Final project: Children design and present their own "AI invention" using craft materials. Capstone Project.
👦 Ages 7–9: Junior Coders
Building logical thinking through classification, decision trees, and data exploration.
Month 1: Animal Detective
Using 30 animal trait cards to sort animals into Mammals, Birds, or Reptiles based on physical features. AI Concept: Supervised Learning.
Month 2: Guess Who? AI Edition
Playing a modified Guess Who where students draw a branching map of their Yes/No questions. AI Concept: Decision Trees.
Month 3: The Human Neural Network
A group of kids acts as "Neurons," passing color-coded strings to decide if an image is a cat or dog. AI Concept: Neural Networks.
Month 4: The Recipe Challenge
Writing precise "recipes" (algorithms) for everyday tasks. Testing them on a partner who follows them literally. AI Concept: Algorithm design.
Month 5: Maze Runner
Navigating physical mazes using different strategies. Which path is shortest? AI Concept: Search algorithms.
Month 6: Loop the Loop
Using physical "Repeat" and "If/Then" cards to build paper-based programs. AI Concept: Control flow & loops.
Month 7: The Prediction Game
Using past data (weather cards) to predict tomorrow's weather. AI Concept: Prediction models.
Month 8: Cluster Kingdom
Grouping fantasy characters into kingdoms based on shared traits without labels. AI Concept: Unsupervised Learning.
Month 9: The Feedback Machine
Building a simple "reward/punish" system for a paper robot. AI Concept: Reinforcement Learning basics.
Month 10: The Rumour Game
How data changes as it passes through people. AI Concept: Data integrity & noise.
Month 11: Privacy Shield
What information should you share online? Building a "Privacy Shield" poster. AI Concept: Data privacy.
Month 12: My Smart Solution
Final project: Design an AI-powered solution for a school problem. Capstone Project.
🧑 Ages 10–11: Logic Builders
Deepening understanding through clustering, information gain, and weighted decision making.
Month 1: Monster Mapping
Grouping 25 unique monsters without labels. Students explain their reasoning. AI Concept: Unsupervised Learning & Clustering.
Month 2: The Information Game
Competing to identify a secret object in the fewest questions. AI Concept: Information Gain.
Month 3: Feature Importance
Using a physical weight scale to decide which data features matter most. AI Concept: Feature Weighting.
Month 4: Binary vs Linear
Comparing search strategies using physical card decks. Which is faster for finding a number? AI Concept: Search efficiency.
Month 5: The Sorting Tournament
Racing to sort cards using Bubble Sort vs. Merge Sort. AI Concept: Sorting algorithms.
Month 6: Code Blocks
Building complex sequences using interlocking physical code blocks. AI Concept: Programming logic.
Month 7: Training Data Lab
Creating "training sets" to teach a paper classifier. What happens with bad data? AI Concept: Data quality.
Month 8: K-Means Clustering
Physically performing K-means clustering on a large mat using tokens. AI Concept: K-Means algorithm.
Month 9: The Error Correction Race
Simulating backpropagation by adjusting physical "Weight" sliders after each error. AI Concept: Backpropagation basics.
Month 10: The Bias Audit
Analyzing a fictional school admission dataset to find hidden bias. AI Concept: Algorithmic fairness.
Month 11: The Ethics Debate
Debating real-world AI scenarios using Ethics Debate Cards. AI Concept: Responsible AI.
Month 12: AI for My Community
Final project: Design an AI solution for a local community problem. Capstone Project.
👩🎓 Ages 12–13: AI Thinkers
Exploring algorithmic bias, complex flowcharts, and data auditing.
Month 1: The Bias Board
Playing a board game where the "rules" unfairly favor certain players. Spotting and rewriting unfair algorithms. AI Concept: Algorithmic Bias.
Month 2: Branching Logic Lab
Designing complex flowcharts using interlocking physical blocks and "If/Then/Else" toggles. AI Concept: Logical flow control.
Month 3: The Bias Detective
Auditing a fictional dataset binder to find and "clean" hidden patterns of bias. AI Concept: Data cleaning & auditing.
Month 4: The Complexity Timer
Measuring how long different algorithms take as data grows. AI Concept: Time complexity (Big O).
Month 5: Graph Theory Puzzles
Solving physical network puzzles (shortest path, minimum spanning tree). AI Concept: Graph algorithms.
Month 6: The Encryption Challenge
Encoding and decoding secret messages using physical cipher wheels. AI Concept: Cryptography basics.
Month 7: Ensemble Voting
Building 3 different decision trees and combining their "votes" for accuracy. AI Concept: Ensemble methods.
Month 8: The Overfitting Trap
Training a model too much on limited data and watching it fail on new data. AI Concept: Overfitting vs. generalization.
Month 9: Recommendation Engine
Building a physical "Book Recommendation" system using student preferences. AI Concept: Collaborative filtering.
Month 10: AI in Healthcare
Exploring how AI helps doctors diagnose diseases. AI Concept: AI applications.
Month 11: The AI Policy Maker
Drafting an "AI Policy" for a fictional country using policy templates. AI Concept: AI governance.
Month 12: TED-Style Presentation
Final project: Present a 5-minute "TED Talk" on an AI topic of their choice. Capstone Project.
🎓 Ages 14–16: Tech Pioneers
Mastering reinforcement learning, ensemble models, and real-world AI ethics.
Month 1: Reinforcement Learning Lab
Playing Hexapawn against a "paper-based AI." Students train it by removing beads for losing moves. After 20 games, the AI becomes unbeatable. AI Concept: Reinforcement Learning.
Month 2: Decision Forest
Building 3 different decision trees for the same data and combining their "votes." AI Concept: Random Forests & Ensembles.
Month 3: Backpropagation Race
Simulating the "Backward Pass." Students adjust physical weight sliders to correct predictions. AI Concept: Backpropagation.
Month 4: The NP-Hard Challenge
Attempting to solve the "Travelling Salesman Problem" with physical maps. AI Concept: Computational complexity.
Month 5: Genetic Algorithms
Evolving solutions to a puzzle by "breeding" the best answers. AI Concept: Evolutionary computation.
Month 6: Simulation Lab
Building a physical simulation of traffic flow and optimizing it. AI Concept: Agent-based modelling.
Month 7: Convolutional Filters
Using physical "filter cards" to detect edges and patterns in images. AI Concept: CNN basics.
Month 8: Natural Language Processing
Building a physical "sentiment analyzer" that rates sentences as positive or negative. AI Concept: NLP fundamentals.
Month 9: Transfer Learning
Taking a trained "model" from one task and applying it to another. AI Concept: Transfer Learning.
Month 10: AI & Climate Change
Designing AI solutions for environmental challenges using scenario cards. AI Concept: AI for social good.
Month 11: The Turing Test Debate
Debating whether machines can truly "think." AI Concept: Philosophy of AI.
Month 12: Capstone: My AI Startup
Final project: Students pitch a full AI startup idea—problem, solution, data, and ethics plan. Capstone Project.
🎯 Learning Outcomes (After 12 Months)
- ✅ Understand core AI concepts (Machine Learning, Neural Networks, Clustering).
- ✅ Build and test physical "algorithms" and decision trees.
- ✅ Recognize and address algorithmic bias in data.
- ✅ Apply computational thinking to real-world problems.
- ✅ Discuss AI ethics, privacy, and responsible technology use.
- ✅ Complete a capstone project demonstrating AI problem-solving skills.