Dr. Muralidhar Kurni;Dr. Srinidhi Hiriyannaiah;Dr. Srinivasa K. G.
Synopsis "AI Systems Development using LLMs"
Large language models have rapidly transformed artificial intelligence, natural language processing, and modern machine learning, making them essential tools for modern software development. This book is your practical roadmap to understanding these technologies and building intelligent, real-world AI applications.This book systematically covers the essential concepts needed to build, scale, and secure intelligent systems. It begins with the foundations of large language models, scaling laws, ethical considerations, and developer tools like LangChain, LlamaIndex, and Ollama. Next, it guides you through prompt engineering, reasoning techniques, and semantic vector search using custom embeddings. You will then learn how to design advanced retrieval-augmented generation (RAG) systems with vector databases like ChromaDB, FAISS, and Weaviate, alongside conversational memory and evaluation frameworks. Finally, the book covers autonomous AI agent orchestration, multimodal models such as GPT-4o and LLaVA, cloud-to-edge deployment, optimization techniques like LoRA and quantization, prompt security, and emerging standards such as the model context protocol.By the end of this book, readers will be well-equipped to design, deploy, and secure production-grade AI systems, possessing the practical skills required to solve complex real-world engineering challenges. They will learn to build scalable, secure, and trustworthy LLM applications for academic, industrial, and entrepreneurial settings.WHAT YOU WILL LEARN¿ Master LLM foundations, scaling, and LangChain ecosystem framework tools.¿ Orchestrate multi-agent systems with ReAct workflows and safety interlocks.¿ Build conversational and RAG applications using vector databases and evaluation frameworks.¿ Develop, orchestrate, govern, and secure task-oriented AI agents.¿ Deploy and optimize scalable, secure, and multimodal LLM applications.¿ Implement semantic chunking across ChromaDB, FAISS, and Weaviate databases.WHO THIS BOOK IS FORThis book is intended for undergraduate and postgraduate students, AI/ML engineers, data scientists, software developers, researchers, system architects, cloud engineers, educators, startup teams, and professionals seeking to build practical applications using large language models.
