AI Foundations
High school pathway: representation, classical ML, generative systems, and civic impact — capped by Operator Skills (prompt systems, hallucination control, thresholds, personal AI playbook).
Unit 1
Intelligence, Representation & Reasoning
What we mean by AI systems; how representation shapes reasoning.
Essential question: How do the representations we choose constrain what an AI system can do?
Defining AI Without the Hype
50 min · 1 quiz items · 1 labs
Contrast narrow AI with popular AGI narratives
Representation Matters
50 min · 1 quiz items · 1 labs
Give examples of how feature choices change model behavior
Classical ML Intuitions
55 min · 1 quiz items · 1 labs
Compare decision trees, nearest neighbors, and linear separators conceptually
Unit 2
Generative AI Literacy
How genAI works at a systems level; verification, IP, integrity, and policy.
Essential question: How should students and citizens work with generative systems responsibly?
Unit 3
Specialization Pathways
Depth tracks: neural nets, NLP intuition, vision ethics, public AI audit capstone.
Essential question: Where do you want to go deeper?
Neural Nets & Overfitting
50 min · 1 quiz items · 1 labs
Explain layers, weights, and overfitting in plain language
NLP: Tokens & Evaluation
50 min · 1 quiz items · 1 labs
Describe tokens as pieces of text models process
Vision Datasets & Ethics
50 min · 1 quiz items · 1 labs
Connect perception systems to training data choices
Capstone: Public AI System Audit
55 min · 1 quiz items · 1 labs
Audit a real public AI system using purpose, data, metrics, and impacts
Unit 4
Operator Skills
The high-school capstone skill stack: prompt systems, hallucination control, threshold decisions, and a personal AI playbook you can use at work and college.
Essential question: What does it mean to operate AI systems competently — not just consume them?
Prompt Systems, Not Spells
55 min · 3 quiz items · 1 labs
Build multi-step prompt systems (plan → draft → critique → revise)
Catching Confident Nonsense
55 min · 3 quiz items · 2 labs
Distinguish supported, false, and unverifiable generative claims under time pressure
Thresholds & Tradeoffs
55 min · 3 quiz items · 2 labs
Explain false positives vs false negatives with a concrete AI policy example
Privacy, Power & Policy
50 min · 2 quiz items · 1 labs
Map data flows in a typical student AI workflow
Capstone: Personal AI Playbook
55 min · 2 quiz items · 1 labs
Publish a personal AI operator playbook covering workflows, refuse lines, and verification