Название: Generative Programming: Building the Next Generation of Software with AI
Автор: Ajit Singh
Издательство: Independently published
Год: November 8, 2025
Страниц: 340
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

"Generative Programming: Building the Next Generation of Software with AI" is a comprehensive and practical guide designed to demystify the principles, tools, and techniques behind the generative AI revolution in software development. This textbook serves as a one-stop resource for students, educators, and professionals, taking them on a structured journey from foundational concepts to the deployment of sophisticated AI-powered applications.

Key Features of This Book:

1. Globally Relevant Curriculum: The topics covered are universal, making the book suitable for students and professionals across the globe.
2. Beginner to Advanced Progression: The book starts with the absolute basics and gradually builds up to advanced topics like model fine-tuning and MLOps, ensuring a smooth learning curve.
3. Hands-On Practical Approach: Every chapter is packed with code examples, practical exercises, and step-by-step tutorials to reinforce learning. The motto is "learn by building."
4. Real-World Case Studies: In-depth case studies are presented throughout the book to illustrate how generative programming is used to solve real business problems in various industries.
5. Comprehensive Capstone Project: The final chapter guides the reader through building a complete, end-to-end generative AI application from scratch, including full working code and deployment steps.
6. Clarity and Simplicity: Complex concepts are explained in the simplest and most intuitive manner possible, using analogies and real-life examples to aid understanding.
7. Focus on Modern Tools: The book provides practical knowledge of essential and up-to-date tools and frameworks like LangChain, LlamaIndex, Hugging Face, and major cloud AI APIs.
8. Holistic Coverage: It covers the entire lifecycle of a generative AI application—from ideation, design, and model selection to implementation, deployment, monitoring, and ethical considerations.

The philosophy behind this book is simple: learn by doing. Generative Programming is not a spectator sport. True understanding comes from hands-on experimentation, from building, breaking, and refining. Therefore, every chapter is infused with practical examples, code snippets, hands-on exercises, and real-world case studies. We will move from the foundational "what" and "why" to the intricate "how," culminating in a full-fledged capstone project that synthesizes all the concepts learned.

We will journey from the basic building blocks of generative models—tokens, embeddings, and attention mechanisms—to the sophisticated architectures of Transformers and GANs. We will master the art and science of Prompt Engineering, the new language of developer-AI interaction. We will explore powerful frameworks like LangChain and Hugging Face that have democratized access to these technologies. We will not shy away from the critical, real-world challenges of fine-tuning, deployment, MLOps, and the all-important considerations of ethics and responsible AI.

To Whom This Book Is For:

This book is intended for a broad audience, catering to both beginners and advanced learners:

1. Software Developers and Professionals: Engineers looking to upskill and integrate generative AI capabilities into their workflow will find this book an invaluable practical guide.
2. AI/ML Enthusiasts and Beginners: Individuals with a basic programming background can use this book as a structured entry point into the exciting world of generative AI.
3. Educators and Instructors: The book's logical chapter progression, case studies, and hands-on labs make it an ideal resource for teaching a course on generative programming or applied AI.






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