Curriculum

AI Foundations

AIV 101–112: the foundational concepts, vocabulary, and context every AI learner needs.

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Courses

1
AIV 101 — Understanding Artificial IntelligenceMost people use AI every day without knowing how it actually works. This course changes that, covering everything from how machines learn to why ChatGPT sometimes makes things up.
2
AIV 102 — How AI WorksMost people use AI every day without knowing what it's actually doing. This course opens the hood and shows you the real mechanics, from raw training data to the probability math behind every output.
3
AIV 103 — The History of Artificial IntelligenceA story-driven survey of AI from the 1956 Dartmouth Workshop to today's agentic AI. Designed for high-school and intro-college students with no CS background — concepts and history over math. Capstone: build and deploy a live interactive AI development timeline.
4
AIV 104 — Understanding Large Language ModelsA hands-on, project-based introduction to how modern LLMs actually work — from tokens to inference — for students who have completed AIV 101–103.
5
AIV 105 — Generative AI FundamentalsA hands-on K-12 introduction to generative AI. Students learn how text, image, audio, video, and code generation actually work, practice prompting real AI tools every unit, and finish with a multimodal capstone combining three GenAI technologies.
6
AIV 106 — AI Vocabulary & ConceptsA hands-on beginner's course through the vocabulary of modern AI. Read short definitions, lock them in with flashcards, then actually try each concept in a real AI tool. Culminates in a personal AI glossary the student builds with an AI agent.
7
AIV 107 — AI Models & the AI EcosystemA ground-level map of the AI landscape: what models actually are, who builds them, how the infrastructure works, and how to choose the right one for any job.
8
AIV 108 — AI Strengths, Weaknesses & HallucinationsMost people trust AI output if it sounds confident. This course explains why that's the wrong instinct, and gives you a practical system for catching AI errors before they matter.
9
AIV 109 — Responsible AIAI systems fail in specific, documented ways — through biased training data, privacy violations, synthetic media fraud, and rubber-stamp oversight. This course teaches you to recognize those failure modes and build the governance structures that prevent them.
10
AIV 110 — AI Privacy & Security FundamentalsMost people worry about AI making mistakes. The bigger risk is AI leaking your company's secrets, getting hijacked by attackers, or memorizing data it shouldn't. This course explains how that happens and what to do about it.
11
AIV 111 — The Economics of Artificial IntelligenceMost people know AI is expensive. This course shows you exactly why, how to measure it, and what it means for the economics of any AI product.
12
AIV 112 — The Future of AIA hands-on, source-grounded survey of the AI frontier and how to reason about where it's going. Students learn what exists today across agents, robotics, autonomous systems, personal AI, and AI-native companies — and end the semester by writing a defensible five-year AI technology forecast.