AI Literacy
Most people meet AI through the headlines: a new model "beats the bar exam," a chatbot "goes rogue," a startup raises a billion dollars. It is loud, it is fast, and it is easy to feel either dazzled or left behind.
This course fixes that. By the end you will understand what AI really is, how it works, where it already touches your life, and how to think about it critically, all before you ever try to operate or build with it. No technical background required. No math. No code.
The arc
This course moves in four movements. Each one builds on the last.
| Movement | You will be able to |
|---|---|
| Demystify | Separate what AI really is from the hype and the science fiction |
| Understand | Explain, in plain language, how an AI system is built and what happens inside a chatbot |
| Recognize | Spot AI in your daily life, name the major players, and read an AI headline without getting lost |
| Engage | Think about AI as an informed, responsible citizen and professional |
Strip away the myths, grasp how it works, spot it in the wild, and engage with it responsibly.
The bar this course clears
When you finish, you should be able to pick up a current AI news article and actually follow it: recognize the model families and companies it names, decode the vocabulary (parameters, tokens, context window, benchmarks), and understand why a stronger model keeps shipping every few months. That is what we mean by literacy.
The lessons
- What Is AI? Myths vs. Reality — the Hollywood version versus the real thing
- How AI Evolved — three waves, and why scaling keeps making models better
- How Machines Learn — data to patterns to prediction, with zero equations
- The 5-Layer AI Stack — from energy and chips to models and apps, and where value sits
- What's Inside a Chatbot — next-token prediction, explained without jargon
- AI You Already Use — maps, feeds, filters, assistants, the models hiding in plain sight
- What AI Can and Can't Do Today — the capability ladder and where we really are
- How to Read an AI Headline — a lab: decode the words that saturate every AI article
- Who's Who in AI — the labs and model families: GPT, Claude, Gemini, Llama
- The Risks — bias, hallucinations, misinformation, and deepfakes
- AI & Society — your data, jobs, and the ethics questions worth asking
- First Contact + Your AI Code of Conduct — a lab: your first guided conversation, and your personal charter
How this course is taught
Concept-first and almost entirely hands-off. You will not be pushed to operate tools yet. Two practical "literacy labs" (Lesson 8, decoding a real headline, and Lesson 12, your first conversation) anchor everything else.
Start with What Is AI? Myths vs. Reality.