LLM Prompt Engineering for Developers

Table of Contents

1. Preface
2. From NLP to Large Language Models
3. Introduction to Prompt Engineering
4. OpenAI GPT and Prompting: An Introduction
5. Setting Up the Environment
6. Few-Shot Learning and Chain of Thought
7. Chain of Thought (CoT)
8. Zero-Shot CoT Prompting
9. Auto Chain of Thought Prompting (AutoCoT)
10. Self-Consistency
11. Transfer Learning
12. Perplexity as a Metric for Prompt Optimization
13. ReAct: Reason + Act
14. General Knowledge Prompting
15. Introduction to Azure Prompt Flow
16. LangChain: The Prompt Engineer's Guide
17. A Practical Guide to Testing and Scoring Prompts
18. General Guidelines and Best Practices
19. How and Where Prompt Engineering Is Used
20. Anatomy of a Prompt
21. Types of Prompts
22. Prompt Databases, Tools, and Resources
23. Afterword