Prompt Engineering 101
Learn the art and science of communicating with Large Language Models. This course will teach you how to craft prompts that guide AI to generate accurate, creative, and useful results, turning you into an expert communicator for the new age of technology.
Module 1
The Core Idea: Guiding the Prediction Engine
This module introduces the foundational concept of prompt engineering. You'll learn that LLMs are powerful prediction engines and that your prompt is the guide that steers those predictions. We'll cover the essential configurations and the mindset needed to get started.
Module 2
Core Prompting Techniques
This module covers the fundamental techniques every prompt engineer must know. These methods are the building blocks for all advanced prompting strategies.
Module 3
Advanced Reasoning Techniques
For complex problems, you need to guide the model's reasoning process. These techniques unlock the AI's ability to solve multi-step problems that require logic and planning.
Module 4
Code Prompting: Your AI Pair Programmer
LLMs are incredibly powerful tools for developers. This module teaches you how to use prompts to speed up your coding workflow.
Module 5
Best Practices for Expert Prompting
Becoming an expert prompt engineer is an iterative process. Here are some key best practices to keep in mind.
Frequently Asked Questions
Your common questions about prompt engineering, answered.
Learn More
Here’s a curated list of sources to learn about prompt engineering. It covers everything from beginner guides to academic-level surveys and is useful for casual users, developers, and researchers.
Starting Guides & Tutorials
- DAIR.AI Prompt Engineering Guide: A community-driven, comprehensive guide-hub that collects many of the latest papers, tutorials, tools and best practices.
- LearnPrompting.org: A free, well-structured online guide to generative AI and prompt engineering.
- OpenAI Prompt Engineering Documentation / Guide: This official guide lays out core principles and best practices.
- Google Prompt Engineering Guide: A practical guide for developers using Google’s AI services.
Courses & Structured Learning Paths
- DeepLearning.AI in partnership with OpenAI: “ChatGPT Prompt Engineering for Developers” a short, practical course.
- Vanderbilt University on Coursera: “Prompt Engineering for ChatGPT” a beginner-friendly course with structured modules.
- Other curated course lists like this one from Analytics Vidhya can highlight a mix of free and paid offerings.
Academic & Deep-Dive Surveys / Papers
- A Systematic Survey of Prompt Engineering in Large Language Models (2024): A peer-reviewed survey on methods, applications, and limitations.
- The Prompt Canvas: A Literature-Based Practitioner Guide (2024): Synthesizes techniques into a unified practical framework.
- A Survey of Prompt Engineering Methods for Different NLP Tasks (2024): Examines methods across various NLP tasks.
Practical & Opinion-Driven Guides / Blogs
- cognativ.com: An up-to-date article offering practical techniques geared for real-world AI tools.
- Medium: A quick, digestible article on good practical habits for writing prompts.
- The Generative Programmer: Broader AI resource lists to stay updated with evolving tools and practices.
Recommendations on What to Read / Do First
- If you’re new: start with LearnPrompting.org or the DAIR.AI guide.
- If you prefer guided learning: take the DeepLearning.AI or Vanderbilt University course.
- Once you’re comfortable: skim one of the academic surveys to get a deeper, principled understanding.
- For long-term skill: follow blogs and curated resource lists to stay updated as prompt engineering evolves rapidly.