LLM Fundamentals Path

How LLMs work, tokens and context, limits, calling an API, and choosing models.

5 lessons · about 42 minutes of reading

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1. 1

   How Large Language Models Work: A Practical Introduction

   Understand tokens, next-token prediction, transformers, and the training stages behind modern LLMs, without the heavy math.

   8 min read

2. 2

   LLM Tokens, Context Windows, and Sampling Explained

   Count tokens, understand context limits and cost, and learn what temperature and top-p control.

   8 min read

3. 3

   LLM Hallucinations, Limitations, and Responsible Use

   Learn why LLMs make things up, how to reduce errors, and the privacy, bias, and oversight issues to plan for.

   8 min read

4. 4

   Calling an LLM API with Python: Your First Request

   Make your first LLM API call with the Anthropic Python SDK, handle conversations, read usage, and handle errors.

   9 min read

5. 5

   Choosing and Evaluating an LLM for Your Use Case

   Pick a model by quality, speed, cost, and constraints, and compare candidates with a small test set of your own.

   9 min read