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This book is a hands-on guide designed to help readers understand, build, and deploy powerful AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic systems, and intelligent chatbots.
Starting with the fundamentals--LLM architecture, tokenization, APIs, and fine-tuning--the book gradually builds toward complex, integrated systems. Readers will learn to implement RAG pipelines using vector databases like FAISS and Pinecone, develop autonomous AI agents that complete multi-step tasks, and create real-world chatbots that understand and adapt to user needs. The approach is project-driven: each chapter includes visual explanations, step-by-step code walkthroughs, and deployment-ready examples. From building a personal assistant that searches your notes to creating a scheduling agent, every project reinforces both technical skills and applied understanding. It emphasizes clarity, inclusivity, and real-world relevance--helping readers move confidently from basic understanding to complex applications.
Whether you're exploring Agentic AI or looking to build production-ready systems, this book gives you the tools to turn curiosity into capability--and innovation into impact.
What you will learn:
Who this book is for:
Machine Learning engineers, data scientists, and AI professionals interested in learning how to build real-world AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent chatbots.
Ajay Rawat is a Data Engineer at the Hartree Centre, STFC, UKRI, with over 20 years of experience spanning academia, industry, and professional training. His expertise includes data engineering, cloud computing, AI/LLMs, and big data technologies. A former Assistant Professor, Ajay has delivered 200+ global trainings for organizations like Google, Citibank, and Walmart, and authored research in cloud computing, fault tolerance, and AI-driven systems. He holds a Ph.D. in Computer Science and Engineering and multiple certifications across Databricks, Google Cloud, and Confluent. He is based in London, UK.
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