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

Document Type

Book

Source of Publication

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

Publication Date

9-1-2026

Abstract

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.

ISBN

[9781041041160, 9781041041184, 9781003626909]

Publisher

Chapman and Hall/CRC

First Page

1

Last Page

221

Disciplines

Computer Sciences

Keywords

Computer science (0.55) | Software deployment (0.49) | Engineering ethics (0.46) | Perspective (graphical) (0.43) | Resource (disambiguation) (0.42) | Generative grammar (0.4) | Work (physics) (0.39) | Management science (0.39) | Architecture (0.33) | Domain-specific language (0.32) | Modeling language (0.32) | Engineering (0.32) | Data science (0.3) | Model-driven architecture (0.3) | Software engineering (0.29) | Pattern language (formal languages) (0.29) | Engineering management (0.29) | Power (physics) (0.27)

Scopus ID

105051588069

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Bronze: This publication is openly available on the publisher’s website but without an open license

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