Large Language Models and Prompt Engineering: A Comprehensive Guide with Practical Applications
暫譯: 大型語言模型與提示工程：結合理論與實務應用的完整指南

Kuhail, Mohammad Amin, Tubishat, Mohammad, Kohail, Sarah

Large Language Models and Prompt Engineering: A Comprehensive Guide with Practical Applications

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商品描述

This book provides a structured and accessible introduction to the theory, design, and real-world use of large language models (LLMs). As generative AI systems become embedded across industries, this book offers readers a balanced perspective that combines technical foundations with practical guidance and critical reflection.

Beginning with the fundamentals of LLMs and prompt engineering, this book progressively explores advanced prompting techniques, application and interaction frameworks, and the underlying architectures that power modern language models. Dedicated chapters examine how LLMs are being applied in high-impact domains such as healthcare, customer support, and education, highlighting design principles, implementation considerations, and illustrative case studies. The book also addresses model fine-tuning, evaluation methods, and the ethical, social, and regulatory challenges associated with deploying LLMs at scale.

This book supports readers in:

- Understanding prompt engineering strategies and application frameworks

- Gaining insight into contemporary LLM architecture and capabilities

- Designing and evaluating LLM-based systems across real-world domains

- Considering ethics, safety, and human-centered aspects of LLM deployment

This book is a practical, accessible resource for those seeking to work thoughtfully and responsibly with LLMs in both academic and applied settings.

商品描述(中文翻譯)

本書以結構化且易於理解的方式，介紹大型語言模型（large language models，LLMs）的理論、設計與實際應用。隨著生成式 AI 系統逐漸融入各個產業，本書提供兼具平衡性的觀點，結合技術基礎、實務指引與批判性思考。

本書從 LLMs 與提示工程（prompt engineering）的基礎開始，逐步探討進階提示技術、應用與互動框架，以及支援現代語言模型運作的底層架構。書中專章分析 LLMs 在醫療保健、客戶支援與教育等高影響力領域的應用，說明設計原則、實作考量與具體案例研究。本書也涵蓋模型微調（fine-tuning）、評估方法，以及大規模部署 LLMs 所涉及的倫理、社會與法規挑戰。

本書協助讀者：

- 了解提示工程策略與應用框架
- 深入認識當代 LLM 架構與能力
- 設計並評估應用於實際領域的 LLM 系統
- 思考部署 LLM 時的倫理、安全性與以人為本等面向

對於希望在學術與實務環境中，以審慎且負責任的方式運用 LLMs 的讀者而言，本書是一份實用且易於理解的資源。

作者簡介

Mohammad Amin Kuhail is an academic and researcher specializing in human-computer interaction and applied artificial intelligence. He earned his Ph.D. in Software Development from the IT University of Copenhagen, Denmark, and holds an M.Sc. in Software Engineering from the University of York, United Kingdom. He is also an IEEE AI Ethics (CertifAIEd) Authorized Lead Assessor, reflecting his expertise in responsible and human-centered AI. Kuhail is currently an Associate Professor at Zayed University's College of Technological Innovation in the United Arab Emirates, where he teaches undergraduate and graduate courses on web technologies, human-computer interaction, and database systems. Alongside teaching, Kuhail leads research on LMMs, chatbot technologies, human-AI interaction, and user behavior. His work examines technical design challenges and the societal implications of AI adoption across domains such as education, healthcare, and digital services. Since joining Zayed University in August 2019, he has contributed to curriculum development, interdisciplinary research, and academic leadership. Previously, he served for 6 years as an Assistant Teaching Professor at the University of Missouri-Kansas City (UMKC), USA, where he received a teaching award in 2018.

Mohammad Tubishat is an Assistant Professor at Zayed University College of Technological Innovation. Tubishat received his Ph.D. in Computer Science (Artificial Intelligence and Natural Language Processing) from the University of Malaya, Malaysia. In addition, he received master's and bachelor's degrees in Computer Science from Yarmouk University, Jordan. Before joining Zayed University, he worked at different universities, including Yarmouk University in Jordan, Taibah University in KSA, Asia Pacific University of Technology and Innovation in Malaysia, and Skyline University College in the UAE. He has been teaching different computer science courses for undergraduate and graduate programs. Tubishat's research areas are Artificial Intelligence, Machine Learning, Sentiment Analysis, Natural Language Processing, and Optimization Algorithms. He has published several peer-reviewed papers in top-ranked journals and conference proceedings.

Sarah Kohail is an Assistant Professor at Zayed University, Abu Dhabi. She holds a Ph.D. in Computer Science from the University of Hamburg and worked as a Research Assistant for several years. She has a deep academic foundation in graph-based text representations, text summarization, and semantic similarity, which she has applied in research and industry. Before joining Zayed University, Kohail spent several years in industry as a Senior Data Scientist, where she developed advanced NLP models, including recommendation systems and knowledge graphs. Her current research focuses on Arabic text detoxification, context-aware anonymization of legal texts, and the application of AI across various domains.

Maha Hadid is an experienced educator with a robust academic background and more than 15 years of teaching experience. Currently a senior instructor at Zayed University in the United Arab Emirates, she holds a Master of Science in Information Sciences and Systems from the University of Marseille, France. Hadid brings extensive expertise to teaching undergraduate IT courses, specializing in system design, database management, and data analysis. In addition to her teaching, she has co-authored a book on object-oriented programming and machine learning. Her professional credentials include being a Fellow of the Higher Education Academy (UK) and a Certified Scrum Master. She has demonstrated exceptional skills in instructional design, developing both blended and classroom-based courses through extensive training in pedagogy and learning theories. Hadid's current focus involves leveraging advanced prompt engineering and low-code system design to develop practical applications across various disciplines.

作者簡介(中文翻譯)

Mohammad Amin Kuhail 是一名學者與研究人員，專長為人機互動（human-computer interaction）與應用人工智慧（applied artificial intelligence）。他在丹麥哥本哈根 IT University 取得 Software Development 博士學位，並持有英國 University of York 的 Software Engineering 碩士學位。他同時也是 IEEE AI Ethics（CertifAIEd）認證的 Authorized Lead Assessor，展現其在負責任且以人為本的 AI 領域之專業。目前，Kuhail 任職於阿拉伯聯合大公國 Zayed University 的 College of Technological Innovation，擔任副教授，教授網頁技術、人機互動與資料庫系統等大學部及研究所課程。除了教學之外，Kuhail 也帶領 LMMs、聊天機器人技術、人機互動，以及使用者行為等領域的研究。他的研究探討技術設計所面臨的挑戰，以及 AI 採用在教育、醫療保健與數位服務等領域所帶來的社會影響。自 2019 年 8 月加入 Zayed University 以來，他持續參與課程設計、跨領域研究與學術領導工作。在此之前，他曾於美國 University of Missouri-Kansas City（UMKC）擔任教學助理教授長達 6 年，並於 2018 年獲得教學獎項。

Mohammad Tubishat 是 Zayed University College of Technological Innovation 的助理教授。Tubishat 於馬來西亞 University of Malaya 取得 Computer Science（Artificial Intelligence and Natural Language Processing）博士學位。此外，他也取得約旦 Yarmouk University 的 Computer Science 碩士與學士學位。在加入 Zayed University 之前，他曾任教於多所大學，包括約旦的 Yarmouk University、沙烏地阿拉伯的 Taibah University、馬來西亞的 Asia Pacific University of Technology and Innovation，以及阿拉伯聯合大公國的 Skyline University College。他曾教授大學部與研究所階段的各類 Computer Science 課程。Tubishat 的研究領域包括 Artificial Intelligence、Machine Learning、Sentiment Analysis、Natural Language Processing，以及 Optimization Algorithms。他已在頂尖期刊與會議論文集發表多篇經同儕審查的論文。

Sarah Kohail 是 Zayed University（阿布達比）的助理教授。她持有 University of Hamburg 的 Computer Science 博士學位，並曾擔任研究助理多年。她在以圖為基礎的文字表示法、文字摘要與語意相似度方面具備深厚的學術基礎，並將這些專長應用於研究與業界工作。在加入 Zayed University 之前，Kohail 曾在業界擔任資深資料科學家多年，期間開發先進的 NLP 模型，包括推薦系統與知識圖譜。她目前的研究重點包括阿拉伯文文字去毒化、具備情境感知能力的法律文本匿名化，以及 AI 在各種領域中的應用。

Maha Hadid 是一名經驗豐富的教育工作者，具備扎實的學術背景與超過 15 年的教學經驗。目前，她在阿拉伯聯合大公國的 Zayed University 擔任資深講師，並持有法國 University of Marseille 的 Information Sciences and Systems 理學碩士學位。Hadid 在大學部 IT 課程教學方面具備豐富專業，專長包括系統設計、資料庫管理與資料分析。除了教學之外，她也共同撰寫了一本關於物件導向程式設計與機器學習的書籍。她的專業資格包括英國 Higher Education Academy Fellow，以及 Certified Scrum Master。透過接受教學法與學習理論方面的廣泛訓練，她在教學設計方面展現卓越能力，能夠開發混成式與課堂教學課程。Hadid 目前專注於運用先進的提示工程（prompt engineering）與低程式碼系統設計，在各種學科領域開發實用應用程式。

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