How LLMs Work
Understand how ChatGPT, Claude, and Gemini actually work — tokens, transformers, training, and generation — in 8 beginner-friendly lessons. Free with certificate.
You use ChatGPT, Claude, or Gemini every day. But do you know what actually happens when you type a prompt and hit Enter?
Most people don’t. And that’s fine — until you need to understand why the AI made something up, why the same prompt gives different answers, or why some models are better at coding while others are better at creative writing.
This course explains how large language models work — from the inside. No math, no code, no PhD required. Just clear explanations of the ideas that power the most important technology of our time. Eight lessons that turn you from an AI user into someone who understands what’s happening under the hood.
What You'll Learn
- Explain how text becomes numbers through tokenization and word embeddings
- Describe the transformer architecture and how self-attention works
- Identify the four stages of LLM training: pretraining, SFT, reward modeling, and RLHF
- Apply temperature and top-p settings to control LLM output behavior
- Evaluate why LLMs hallucinate and what mitigation strategies exist
- Compare major LLM models and choose the right one for specific tasks
After This Course, You Can
What You'll Build
Course Syllabus
Frequently Asked Questions
Do I need a computer science or math background?
No. This course explains LLMs using analogies and plain language. We use zero math formulas. If you can use ChatGPT, you can understand how it works.
Will this help me write better prompts?
Yes. Understanding how LLMs process text, why they hallucinate, and how temperature works directly improves your prompting. You'll know why certain prompt techniques work.
Which LLMs does this course cover?
The concepts apply to all LLMs — GPT-4/5, Claude, Gemini, Llama, Mistral, and others. Lesson 8 compares specific models and their strengths.
How long does the course take?
About 2 hours of reading. Each lesson takes 10-20 minutes. No coding or hands-on exercises required — this is a conceptual course.
