This hands-on course will teach you how to integrate cutting-edge AI capabilities into your Spring Boot applications using the Spring AI framework and OpenAI.
You’ll master everything from building your first chat-based app to using Retrieval-Augmented Generation (RAG), Tool Calling, Structured Output Conversion, MCP (Model Context Protocol), and even Speech-to-Text, Text-to-Speech, and Image Generation — all using Java and Spring Boot.
From understanding how LLMs work to deploying production-ready AI features with observability, testing, and advisor-based safety, this course is packed with powerful demos, clean explanations, and practical techniques to bring intelligence to your backend.
Whether you’re a Java developer, Spring enthusiast, or backend engineer exploring Generative AI, this course will guide you step-by-step with best practices and battle-tested code.
What You’ll Learn:
Section 1: Welcome & Hello World with Spring AI
- Understand the Spring AI framework and course roadmap
- Build your first Spring Boot AI app using OpenAI
- Deep dive into ChatModel and ChatClient APIs
Section 2: Prompt Engineering & Structured Output
- Use message roles, prompt templates, and stuffing techniques
- Work with advisors to control AI behavior
- Map AI responses to Java Beans, Lists, and Maps
Section 3: Generative AI & LLM Fundamentals
- Learn about tokens, embeddings, and how LLMs generate text
- Understand attention, vocabulary, and model internals
- Explore static vs positional embeddings and context windows
