AI Basics
To use AI well, you first need to know what it does well and what it does poorly. Once you understand how it works, your questions change, and when your questions change, so do the results.
Artificial intelligence is neither magic nor a being that thinks like a person. It is a computing device that finds patterns in many examples and uses those patterns to produce answers for new inputs. If you understand just this one fact clearly, you can judge when to trust an AI's answer and when to doubt it.
The course runs in this order: how it works (Lessons 1–4), how to talk to it (Lessons 5–6), using it safely (Lessons 7–8), and using it for work and study (Lessons 9–10). There is almost no math. If you are curious about the mathematical background, read Math Basics, Lesson 10, "The Math Behind AI," alongside it.
We do not cover how to use any particular service. Services change every few months, but the nature of a machine that learns from data, and what makes a good question, do not change easily.
- People who have tried AI but get inconsistent answers and are not sure how to ask
- People who want to understand the big picture of how AI works, without equations
- People who use AI for work or study and worry about wrong answers and personal information
- People who need to explain to children or students how to use AI properly
Lessons
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1LESSON
🤖 What Is AI? — Rules and Learning
Traditional programs follow rules written by people; today's AI finds the rules in example data. This one difference explains both AI's strengths and its weaknesses.
14 min -
2LESSON
📊 Machine Learning Basics — Data, Model, Training, Evaluation
Machine learning means collecting data, choosing a model, training it to reduce its error, and evaluating it on data it has never seen. The final evaluation matters most.
15 min -
3LESSON
🧠 Neural Networks, Intuitively — Small Calculations Add Up to Judgment
A single neuron in an artificial neural network does a simple calculation: multiply, add, filter. Stack a huge number of these calculations and you get complex judgments, like recognizing photos and understanding sentences.
18 min -
4LESSON
💬 How Do Large Language Models Produce Text?
A large language model builds sentences one piece at a time, each time choosing "the most plausible piece to come next after the text so far." Once you understand this principle, AI's strengths and weaknesses make sense all at once.
18 min -
5LESSON
✏️ Prompt Basics — Saying Exactly What You Want
A prompt is a work order you give to an AI. With four elements in place — goal, context, constraints and format — you can get far more useful answers from the very same AI.
17 min -
6LESSON
🧩 Advanced Prompting — Roles, Examples, Steps, Format
Add the techniques of roles, examples, steps and format on top of the four basic elements, and you can reliably hand even complex jobs to AI. These techniques are not magic; they are just another name for "clearer instructions."
19 min -
7LESSON
🔍 Hallucination and Verification — How to Doubt What Sounds Plausible
Because AI's answers follow plausibility, content that sounds plausible but is wrong can slip in. If you know which answers are risky and build the habit of checking, you can use AI safely.
17 min -
8LESSON
🛡️ Privacy, Copyright and Ethics — Using AI Responsibly
People who use AI have three responsibilities: protect the information you put in, respect other people's creative work, and check the results before sending them out under your name.
17 min -
9LESSON
🤝 Working with AI — Delegate, Check, Connect
People who use AI well at work break tasks into small pieces and hand the AI the pieces that suit it, decide in advance where to check, and turn frequent tasks into templates they reuse.
17 min -
10LESSON
🌱 Learning Strategies for the AI Era — The Basics Shape Your Questions
AI speeds up learning, but if you hand over your thinking entirely, your skills won't grow. You need the basics to ask good questions and verify the answers. This lesson wraps up the whole site.
16 min