Module 1: Introduction to ChatGPT - Wrap-up
Reviewing the foundations of ChatGPT, GPT history, and the ethical considerations of AI use.
Module 1 Wrap-up: Getting Started
Congratulations! You've completed the first module of the ChatGPT Power User course. You now have a solid foundation in how LLMs work and how to think about them as tools.
What We Covered
- Lesson 1: The Transformer architecture and predictive nature of LLMs.
- Lesson 2: The massive scale and evolution from GPT-1 to GPT-4o.
- Lesson 3: Practical use cases from coding to marketing.
- Lesson 4: Critical limitations like hallucinations and context windows.
- Lesson 5: Staying safe and ethical in an AI-powered world.
Key Vocabulary
| Term | Definition |
|---|---|
| LLM | Large Language Model (e.g., GPT-4). |
| Token | The basic unit of text an AI processes (roughly 0.75 words). |
| Transformer | The specific neural network architecture used by GPT. |
| Hallucination | When an AI confidently states a false fact. |
| RLHF | Reinforcement Learning from Human Feedback. |
Quick Quiz
- What does the "P" in GPT stand for?
- Why should you never paste customer credit card numbers into ChatGPT?
- True or False: ChatGPT understands facts exactly like a human brain does.
Ready for Module 2?
In the next module, we will dive into the Fundamentals. You'll move beyond "chatting" and start learning how to control the engine directly using tokens, context settings, and role prompts.