Most RAG (Retrieval-Augmented Generation) courses stop at loading a few PDFs and asking a simple question, leaving you with a demo but not a production-ready system. This course is designed for backend engineers who want to build reliable, maintainable AI systems that can evolve with real-world data. It treats RAG as a system design challenge, not a prompt trick, guiding you through building a complete, production-grade assistant using Spring AI, PostgreSQL, and Redis.

This Course Offers

• A complete, backend-first approach to designing RAG systems: You will learn to build a RAG system with clear boundaries, explicit pipelines, and production-minded decisions, using Spring AI and Spring Boot.
• Mastery of ingestion pipelines and chunking strategies: You will build repeatable pipelines for PDFs and databases, and learn how chunking strategies directly affect retrieval quality and correctness.
• Expertise in metadata-aware retrieval and vector storage: You will design retrieval pipelines that use metadata to improve search accuracy and store embeddings with clear structure for long-term reliability.
• Knowledge of prompt orchestration and the knowledge lifecycle: You will control LLM behavior with explicit grounding rules and source-aware answers, and safely add, update, and delete data without corrupting retrieval results.

Why We Love This Course

1. It treats RAG as a serious backend system, not a toy. You can tell the course is built for engineers who need to own and evolve AI systems in production, focusing on system design, correctness, and reliability from the start.
2. It follows a progressive, code-based structure. The course builds a single, evolving codebase, exactly like a real backend project, making the learning experience practical and cohesive.
3. It covers the entire RAG lifecycle. The course addresses ingestion, chunking, embedding, retrieval, prompt orchestration, and knowledge lifecycle management, providing a complete picture of what it takes to build a production system.
4. It is built with a strong technological foundation. Using Spring Boot, Spring AI, PostgreSQL, and Redis, the course ensures your skills are built on an enterprise-grade stack, making them directly transferable to professional work.

Building AI systems that can be trusted in production requires a disciplined, backend-first approach. This course provides a clear, practical, and comprehensive path to building that expertise. It is backed by a money-back guarantee if it does not meet your expectations.

• This course is perfect for Java and Spring Boot developers who want to integrate RAG into backend applications.
• It is ideal for backend engineers adding AI capabilities to existing systems.
• The course is also great for developers who care about system design, correctness, and long-term maintainability.

• Basic experience with Java and Spring Boot (REST APIs, configuration, project structure) is required.
• Comfort working with databases and general backend application concepts is needed.
• No prior AI, RAG, or Spring AI experience is required; all concepts are covered from scratch.

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.