All GuidesGuide 01
Beginner • ~1h

LLM Fundamentals

Understand Transformers, tokens, temperature, top-p, and context windows. Free guide to the architecture behind ChatGPT and Claude.

This module moves from intuitive writing to a calibrated approach to prompts, understanding the model's functioning and control levers.

Objectives

01Explain how LLMs produce text from prompts
02Analyze the structure of an effective prompt
03Develop prompts adapted to different business objectives

Contents

Section 01
How LLMs work (Transformer architecture, next-word prediction).
Section 02
Model parameters: temperature, top-p and max_tokens to balance creativity and coherence.
Section 03
Zero-shot, One-shot and Few-shot techniques to calibrate the response.
Section 04
Workshop: creating a business Prompt-Book with before/after comparison.

Skills

Link LLM behavior to its probabilistic mechanics.Choose the prompting technique adapted to the use case.Document a reusable and controllable business prompt.

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Frequently Asked Questions

What is the "LLM Fundamentals" module?+

"LLM Fundamentals" is a Beginner • ~1h-level online training module. Understand Transformers, tokens, temperature, top-p, and context windows. Free guide to the architecture behind ChatGPT and Claude.

Are there any prerequisites for this module?+

Yes, we recommend completing Module 0 before starting this module.

Is this module free?+

Yes, this module is completely free and accessible without a paid subscription.

What will I learn in this module?+

Link LLM behavior to its probabilistic mechanics.. Choose the prompting technique adapted to the use case.. Document a reusable and controllable business prompt..