Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama

By Ali Jafari

Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) are redefining how software systems are built. But most resources either focus on theory - or on shallow demos.

This book bridges the gap.

Building LLM Systems with RAG takes you from Machine Learning fundamentals to deploying scalable, production-ready Generative AI systems using modern tools like LangChain and Ollama.

This is not just another prompt engineering guide.

This is a system-building handbook.

What You'll Learn

You will build a complete mental model of modern AI systems:

Foundations of Machine Learning and Deep Learning

Neural Networks, Transformers, and LLM architecture

Prompt Engineering techniques used in real systems

How RAG reduces hallucinations and improves reliability

Embeddings and vector databases

Chunking strategies that impact retrieval quality

Hybrid search (Sparse + Dense retrieval)

Reranking techniques for precision

Evaluating RAG systems properly

Designing production-ready LLM pipelines

Deploying scalable RAG systems using LangChain and Ollama

Running Local AI models securely and cost-effectively

By the end of this book, you won't just understand LLMs - you'll know how to build reliable AI systems around them.

Who This Book Is For

This book is for:

Software Engineers

Machine Learning Engineers

AI Architects

Technical Founders

Developers moving into Generative AI

You must know Python not Perfessional but minimum syntax understanding.

No PhD required - but curiosity and technical mindset are essential.

From Deep Learning to Production

You will move step-by-step:

Machine Learning
→ Deep Learning
→ Transformers
→ Large Language Models
→ Prompt Engineering
→ Basic RAG
→ Advanced RAG
→ Production Deployment

Each concept builds toward one goal:

Creating scalable, production-grade LLM systems.

What Makes This Book Different?

Unlike many AI books:

It focuses on systems, not just models

It explains why architectural decisions matter

It includes production engineering considerations

It combines theory with practical design

It uses real-world RAG pipelines

It integrates LangChain and Ollama for local AI

This book prepares you for the real world - not just the demo environment.

• Format: Paperback
• Language: English
• ISBN: B0GQLR3BQL
• ISBN13: 9798250073844
• Release Date: February 2026
• Publisher: Independently Published
• Length: 152 Pages
• Weight: 0.81 lbs.
• Dimensions: 0.3" x 8.5" x 11.0"