NeuralQuest

Learn how AI really works by building it: label the data and train a classifier, then investigate how a recommender can quietly narrow what you see.

Level 1

For grown-ups — progress report →A private, on-device snapshot mapped to the skill areas practiced. Export a CSV or print — nothing leaves this device.

Classifier Trainer

Be the teacher: label a handful of examples, watch an AI discover a rule from your labels, then predict what it does on a brand-new example. Find where its training data was unfair and fix it.

Train a classifier →

Concepts — choose a kit

16 kits, from how machines learn to AI in society — each a short round of questions with hints when you need them. Your progress stays on this device.

Kit 1: how_machines_learn_gr45 How machines learn · grades · 25 questions Kit 2: training_your_first_classifier_gr45 How machines learn · grades · 25 questions Kit 3: neural_networks_and_deep_learning_gr56 Neural networks · grades · 25 questions Kit 4: recommendation_systems_and_personalization_gr56 Recommendation systems · grades · 25 questions Kit 5: bias_fairness_and_data_ethics_gr67 Ethics & bias · grades · 25 questions Kit 6: computer_vision_and_image_ai_gr67 Computer vision · grades · 25 questions Kit 7: natural_language_processing_and_ai_communication_gr78 Language AI · grades · 25 questions Kit 8: master_ai_scientist_responsible_ai_capstone_gr78 Review & synthesis · grades · 25 questions Kit 9: Reinforcement Learning and AI Agents How machines learn · grades 4-5 · 25 questions Kit 10: Generative AI and Creative Machines How machines learn · grades 5-6 · 25 questions Kit 11: AI in Society and Everyday Life Ethics & bias · grades 6-7 · 25 questions Kit 12: Future of AI and Emerging Technologies Future of AI · grades 7-8 · 25 questions Kit 13: Cross-Topic Connections Review & synthesis · grades 5-6 · 25 questions Kit 14: Real-World Applications Review & synthesis · grades 6-7 · 25 questions Kit 15: Misconceptions & Reasoning Review & synthesis · grades 6-7 · 25 questions Kit 16: Advanced Synthesis Review & synthesis · grades 7-8 · 25 questions

More ML challenges

Hands-on machine-learning puzzles and extra practice modes:

Recommendation LabCatch filter bubbles and popularity bias. Training LoopLearn when to stop before a model overfits. Does it Generalize?Spot the overfit on data it has never seen. Weigh ItPick the decision that weighs both sides. Mixed practiceRevisit questions from the kits you’ve played. NeuralQuest SprintA calm speed round on what you’ve mastered. ML Quest mapA path through all 16 kits.

Play together

A quick machine-learning face-off for 2–4 players — same device, or an online room by code.

ML Duel (pass-and-play) 2–4 players take turns on one device, or open an online room by code.
NeuralQuest mascot

Meet the cast — the characters who teach this

Each one stands for an idea you’ll practice. Tap a character to read their illustrated story and hear their audio drama.

Explore all the stories →

📚 Books for NeuralQuest

Read the story, print a workbook, or color the cast — free PDFs to read offline or print at home.

Browse all books →

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