LLM Engineering For Beginners A Practical Guide to Large Language Models, Prompt Engineering, APIs, Data Pipelines, RAG

Large language models are becoming an important building block for modern software applications, but learning to engineer with them involves much more than understanding how to write a prompt. LLM Engineering For Beginners provides a practical introduction to the technologies, concepts, and workflows behind modern LLM-powered applications. Starting with the fundamentals of large language models, the book progressively introduces prompt engineering, APIs, application architecture, data engineering, embeddings, vector search, and retrieval-augmented generation. You will learn how to work with LLM APIs, design effective prompts, process and prepare data, generate embeddings, build retrieval pipelines, connect models to applications, and evaluate the quality of generated results. The book also introduces important considerations around security, testing, reliability, cost, and maintainability.Through practical engineering workflows and end-to-end examples, you will move from basic experimentation toward building structured LLM applications that can be expanded and improved over time. Whether you are a developer entering the world of generative AI or an engineer looking to establish a solid foundation in LLM application development, this book provides a clear path from fundamental concepts to practical implementation.

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