River Publishers Series in Computing and Information Science Technology- Mastering Prompt Engineering

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Bol This book explains the principles, structure, and real-world practice of prompt engineering in a way that anyone working with large language models can understand and apply. It is designed for students, educators, and practitioners and includes hands-on exercises that can be tried in tools like ChatGPT. This book explains the principles, structure, and real-world practice of prompt engineering in a way that anyone working with large language models can understand and apply. Rather than treating prompting as a collection of hacks, it walks the reader through how to think about role, context, task, constraints, and examples so that LLMs produce reliable, domain-appropriate outputs. Starting from the basics of “what is a prompt,” the book then connects prompting to how generative AI models actually work, introduces core and advanced prompting patterns (prompt chaining, dynamic templates, tool-augmented prompting), and shows how to evaluate and refine model responses. Designed for students, educators, and practitioners, each chapter includes learning objectives and hands-on exercises that can be tried directly in tools like ChatGPT. Later chapters move from theory to application, demonstrating how to build LLM-powered chatbots and retrieval-augmented generation (RAG) systems, and how to incorporate ethics, safety, and bias awareness into prompt design. By the end, readers will have a reusable toolkit for crafting effective prompts across education, research, business, and technical use cases.

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This book explains the principles, structure, and real-world practice of prompt engineering in a way that anyone working with large language models can understand and apply. It is designed for students, educators, and practitioners and includes hands-on exercises that can be tried in tools like ChatGPT. This book explains the principles, structure, and real-world practice of prompt engineering in a way that anyone working with large language models can understand and apply. Rather than treating prompting as a collection of hacks, it walks the reader through how to think about role, context, task, constraints, and examples so that LLMs produce reliable, domain-appropriate outputs. Starting from the basics of “what is a prompt,” the book then connects prompting to how generative AI models actually work, introduces core and advanced prompting patterns (prompt chaining, dynamic templates, tool-augmented prompting), and shows how to evaluate and refine model responses. Designed for students, educators, and practitioners, each chapter includes learning objectives and hands-on exercises that can be tried directly in tools like ChatGPT. Later chapters move from theory to application, demonstrating how to build LLM-powered chatbots and retrieval-augmented generation (RAG) systems, and how to incorporate ethics, safety, and bias awareness into prompt design. By the end, readers will have a reusable toolkit for crafting effective prompts across education, research, business, and technical use cases.


Productspecificaties

Merk River Publishers
EAN
  • 9788743813668
Maat


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