LLM Engineering & Generative AI · LLM Engineering & Generative AI

Prompt Engineering

This track teaches the skills to design, test, and refine prompts for large language models effectively. You'll learn techniques like zero-shot and few-shot prompting, chain-of-thought reasoning, and structured output formatting. It's for developers, data scientists, and AI enthusiasts who want to build reliable AI-powered applications. By the end, you'll be able to craft prompts that produce consistent, accurate results across various LLM APIs.

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Lesson outline

  1. 1
    System, User, Assistant Roles

    Master the three roles in LLM prompts to set behavior, give inputs, and format outputs. This tutorial covers the mental model, a hands-on walkthrough, and troubleshooting tips.

  2. 2
    Select Few-Shot Examples

    Learn how to select and format few-shot examples for reliable LLM outputs. This lesson covers the core concept, a step-by-step method, hands-on exercise, and troubleshooting — perfect for prompt engineering beginners.

    Prompt Engineering — step-by-step tutorials

    What you will find here

    This track walks through prompt engineering in order — each lesson is server-rendered HTML you can read without JavaScript. Follow the outline, then practice in the browser IDE when a lesson links to runnable code.

    Tutorials vs quizzes and code samples

    Tutorials teach in sequence. For quick checks use quizzes. For copy-paste snippets see code samples. For deeper reading browse articles.