Beginner
Beginner Path
For people who have used AI tools a little but never dug into how they work. This path takes you from zero to confident in about two hours.
Steps 10
Est. time ~2 hours
Prerequisites None
The Path
1
What Is a Large Language Model?
Everything in AI starts here. Understand what an LLM actually is before you learn to use one.
12 min
2
AI, ML, Deep Learning, GenAI — What's the Difference?
These terms are used interchangeably in the news but mean very different things. Get the map straight.
10 min
3
Tokens, Context Windows, and Parameters
You'll hit token limits, context confusion, and parameter talk almost immediately. Know what they mean.
10 min
4
Hallucinations and Limitations
AI makes things up confidently. This page teaches you how to spot it and work around it.
10 min
5
Anatomy of a Good Prompt
The difference between a bad and great AI response is usually the prompt. Learn the structure.
12 min
6
Prompting Patterns That Work
Chain-of-thought, role assignment, few-shot examples — practical patterns you can use today.
12 min
7
Chat Assistants Guide
A tour of ChatGPT, Claude, Gemini, Perplexity — what each is best at, and when to switch.
15 min
8
AI for Writing
The most common beginner use case. Learn how to get drafts, rewrites, and tone changes right.
10 min
9
Working with Images
AI can now read, describe, and generate images. A quick intro to what's possible.
10 min
10
Starter Project: Personal Learning Assistant
Put it all together. A guided first project — build your own study assistant with no code required.
20 min
After This Path
Once you finish these 10 pages, you'll have a solid mental model of how AI works and practical skills for everyday use. The natural next step depends on where you want to go:
- Builder Path — if you want to start building apps with AI
- Manager Path — if you're thinking about AI strategy at work
- AI Tools section — to explore more tools and use cases
- AI Glossary — to look up terms you've encountered
Checklist: Do You Understand This?
- Can you explain what an LLM is to someone who has never heard of it?
- Do you know the difference between AI, machine learning, and generative AI?
- Can you write a prompt that consistently gets better output?
- Do you know when to trust AI output and when to verify it?
- Have you built or tried the personal learning assistant project?