Module 2: How LLMs Work (Simplified)
The Magic Behind the Curtain
Now that you know what LLMs are, let's peek behind the curtain to understand how they work. Don't worry—we'll keep things simple and use plenty of analogies.
What You'll Learn
In this module, you will:
- Understand where training data comes from and what the model learns from it
- Learn how next-word prediction works and why it produces intelligent-seeming responses
- Discover how context and memory function in conversations with LLMs
Module Structure
| Chapter | Topic | Duration |
|---|---|---|
| Chapter 1 | Training on Text Data | 20 min |
| Chapter 2 | Predicting the Next Word | 25 min |
| Chapter 3 | Context and Memory | 20 min |
| Quiz | Module 2 Quiz | 30 min |
Key Concepts Preview
Training
The process of teaching an LLM by showing it massive amounts of text and adjusting its parameters to better predict what comes next.
Tokens
The basic units that LLMs process—usually parts of words. "Understanding" might be three tokens: "under", "stand", "ing".
Probability
How likely the model thinks a word should come next. "The cat sat on the ___" → "mat" (high probability) vs "airplane" (low probability).
Context Window
The amount of text the model can "see" at once—like short-term memory for the conversation.
The Library Analogy
Imagine a person who has read every book in the world's largest library—billions of pages of text. They didn't memorize every sentence, but they developed a deep intuition for how language works.
When you ask them a question, they don't look up the answer in a book. Instead, they generate a response based on patterns they've absorbed from all their reading.
That's essentially how an LLM works.
Why This Matters
Understanding how LLMs work helps you:
- Craft better prompts that get the responses you want
- Recognize limitations inherent in the technology
- Debug problems when the AI gives unexpected results
- Make informed decisions about when to trust LLM outputs
Let's Get Started!
Begin with Chapter 1: Training on Text Data to discover how LLMs learn from text.
Estimated time to complete this module: 1.5-2 hours