Explore AI algorithms through hands-on visualization
Learn artificial intelligence concepts by interacting with real algorithms, lessons, and games. Explore AI ethics, data science, machine learning, search algorithms, and more through hands-on visualization tools designed for high school students.
Each topic includes interactive lessons, visualizations, and quizzes to test your knowledge. Start with AI ethics to understand responsible AI use, then dive into data science and machine learning!
Choose a topic to dive into interactive lessons, games, and visualizations
Learn about bias, fairness, privacy, and how to use AI tools responsibly in your academic and personal life.
Design products with users at the center through empathy, ideation, prototyping, and iterative testing.
Learn to work with data structures, visualize data effectively, and discover patterns through analysis and cleaning techniques.
Interactive lessons and games for ML algorithms including supervised learning, unsupervised learning, NLP, and more with visualizers.
Explore different types of neural networks and their architectures including CNNs, RNNs, LSTMs, GANs, Autoencoders, and Transformers.
Visualize how AI finds paths through trees and mazes using BFS, DFS, UCS, A*, and other pathfinding algorithms.
Learn how AI plays games strategically using the Minimax algorithm with alpha-beta pruning and game tree search.
Understanding how AI systems become unfair and what we can do about it.
Game: Bias Detective - Identify different types of bias in AI scenarios
What makes an AI decision fair? Explore core ethical principles.
Game: Ethics Compass - Rate AI scenarios on an ethical risk slider
How students should interact with AI tools for learning.
Game: AI Use Judge - Label AI usage as responsible, gray area, or unsafe
How AI tools store and infer information from your data.
Game: Digital Footprint Meter - Discover how much private data you reveal
Trace AI’s rise, winters, and breakthroughs with interactive logic gates, perceptrons, and CPU animations.
Learn to understand users through research, personas, and empathy mapping.
Game: Persona Builder - Build personas from user interviews
Generate creative solutions and build prototypes to test ideas.
Game: Solution Sprint - Design user-centered solutions under time pressure
Test designs with users and iterate based on feedback.
Game: Usability Detective - Find and fix usability issues in mockups
What they are and why they matter for AI and computer science.
Game: Data Structure Playground - Organize data into lists, tables, trees, graphs
Learn about hierarchies and decision paths in tree structures.
Game: Folder Tree Builder - Build folder hierarchies and test search efficiency
Networks, connections, and relationships in graph structures.
Game: Graph Your World - Create graphs to model social networks, maps, and more
Reading and interpreting different types of graphs.
Game: Chart Switcher - Toggle datasets through different chart types
Tell compelling stories with data through effective visuals.
Game: Story from a Scatterplot - Interpret patterns and write data stories
How visuals can trick you and how to spot deception.
Game: Spot the Sketchy Graph - Identify deceptive charts and explain what's wrong
Why messy data creates wrong conclusions in AI.
Game: Fix the Dataset - Correct errors, duplicates, and outliers
Human data insight skills - finding patterns without AI.
Game: Manual Clustering Board - Cluster data manually vs. K-means algorithm
Learn how AI learns from labeled examples.
Games: Stock Market Prophet & Spam Filter Trainer
Discover how AI finds patterns without labels.
Game: Color Palette Creator - Use K-means clustering for color palettes
Neural networks and how they learn.
Game: Image Classifier Challenge - Build a neural network to classify images
Natural Language Processing and text AI.
Game: Sentiment Detective - Analyze text sentiment with NLP
Simplifying complex data while keeping information.
Game: Dimension Compressor - Reduce dimensions while preserving variance
How AI learns through trial and error.
Game: Q-Learning Grid World - Train an AI agent with rewards and penalties
Support Vector Machines: Finding optimal boundaries with maximum margin.
Game: Margin Maximizer - Draw decision boundaries to maximize margin
The simplest neural network where data flows forward without loops.
Game: Network Architect - Design your own feedforward network architecture
Networks with memory - perfect for sequences and time series data.
Game: Text Predictor - Predict the next word using sequence memory
Specialized for image processing with filters and pooling layers.
Game: Filter Detective - Match filters to detect edges, blurs, and patterns
Advanced RNN that solves the vanishing gradient problem.
Game: Sequence Memory Master - Test your long-term sequence memory
Two networks compete - generator creates, discriminator judges.
Game: Real or Fake Detective - Identify real vs AI-generated patterns
Compress and reconstruct data through bottleneck layers.
Game: Image Denoiser - Remove noise while preserving image quality
Self-attention mechanism powering GPT, BERT, and modern LLMs.
Game: Attention Master - Identify which words should attend to each other
How AI makes strategic decisions in two-player games using game tree search.
Game: Connect Four - Play against AI using Minimax with alpha-beta pruning
Explores all neighbors at the current depth before going deeper. Guarantees shortest path in unweighted graphs.
Goes as deep as possible down one path before backtracking. Fast but doesn't guarantee shortest path.
Always expands the lowest-cost path first. Finds optimal path in weighted graphs.
Uses both actual cost and estimated distance to goal. Most efficient informed search algorithm.
Only considers estimated distance to goal. Fast but not always optimal.
Combines benefits of BFS and DFS. Memory efficient with guaranteed shortest path.