Mastering Prompt Engineering

Deep Insights for Optimizing Large Language Models (LLMs)

Anand Nayyar, Ajantha Devi Vairamani, Kuldeep Kaswan

• Publisher: Morgan Kaufmann
• Year: 2025
• Topic: Computer Science
• eBook ISBN:
  9780443339059
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach. - Addresses ethical concerns and provides strategies for mitigating bias and ensuring responsible AI practices - Covers foundational concepts, advanced techniques, and the broader landscape of LLMs, equipping readers with a well-rounded understanding - Serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization

Table of contents

• Cover image
• Title page
• Copyright
• Contents
• About the Authors
• Preface
• CHAPTER 1 Basic insights into large language models (LLMs)
• CHAPTER 2 Foundations of prompt engineering
• CHAPTER 3 Familiarity with effective prompt design and process
• CHAPTER 4 Preprocessing and tokenization in prompt engineering
• CHAPTER 5 State-of-the-art techniques in prompt engineering
• CHAPTER 6 Various large language model types
• CHAPTER 7 Tools and platforms for prompt engineering
• CHAPTER 8 Evaluation and refinement of prompt engineering
• CHAPTER 9 Prompt engineering: Ethical considerations and challenges
• CHAPTER 10 Case studies in prompt engineering
• CHAPTER 11 Future trends in large language models and prompt engineering
• Index