Complete GenAI with Java & Spring AI: LLMs, RAG, AI Agents

Want to build real-world Generative AI (GenAI) applications with Java, Spring Boot, Spring AI, RAG and AI Agents—not just experiment with prompts? This course will take you from fundamentals to production-ready AI systems, including RAG pipelines, AI agents, tool calling, chat memory, MCP, observability, prompt engineering, and prompt hacking. Hi there! My name is Ali Gelenler. I'm here to help you learn GenAI using Java and Spring AI from fundamentals to real-world production ready AI architectures and systems with a practical approach. In this course, you will focus on creating AI applications to go beyond AI generated code and implement over 20 use cases using Java and Spring AI together with various AI providers and models, such as Open AI, Google Gemini Vertex AI, Hugging Face, Ollama and Docker Model Runner. You will build AI applications and AI systems using LLMs (Large Language Models), integrate vector databases and embeddings, and design scalable backend architectures for Generative AI. You will learn: Building end-to-end GenAI systems in Java and Spring AI with advanced Spring AI concepts Designing RAG pipelines with vector databases, embeddings, similarity search and semantic search using advanced ingestion and retrieval strategies such as query transformer, query expander, pre/post processors, re-ranker, metadata filtering and dynamic resource updates Creating AI agents with tool/function calling using autonomous and chained workflow agentic systems Implementing chat memory and long-term context with in-memory, jdbc and vector store backends using Spring AI advisors Applying prompt engineering best practices and defend against prompt hacking techniques including prompt injection, jailbreaking and prompt leaking attacks Using MCP (Model Context Protocol) for distributed AI systems, creating MCP Server and MCP client using Spring AI Adding Observability (logs, traces, metrics) to AI applications Learning Gen AI and LLM Fundamentals with Tokenizers, Embeddings, Positional encoding, Transformer architecture, Token prediction and Softmax formula Mapping the Gen AI and LLM Fundamentals into practical solutions Understanding LLM limitations and possible mitigations You will implement 20+ real-world use cases, including: AI-powered assistants: Summarizer, Java Doc generator, Programming helper, Email drafter, Post generator Document Q&A systems with advanced RAG pipelines Security review from architectural diagram AI agent system with multiple tools including Remote Mcp Server tool, Web tool, RAG tool and Diagram extract tool, implementing both autonomous and chained workflow agent systems Multimodal applications including Image-to-Text, Text-to-Image, Speech-to-Text and Text-to-Speech use cases Order status helper with advanced chat memory strategies Production-ready AI systems with monitoring and tracing Technologies & tools you will use: Java & Spring AI Advanced Spring AI concepts: Streaming, Structured output, Chat options, Advisors, Prompt templates OpenAI, Google Gemini (Vertex AI), Hugging Face APIs Ollama & Docker Model Runner for local LLMs Vector databases using PgVector MCP (Model Context Protocol) with MCP Server and MCP Client implementations Observability tools (Grafana, Prometheus, Otlp, Tempo, Jaeger, Loki and Promtail) This is a practical and production-oriented course. You will not just generate code using AI tools—you will learn how to: Design systems Handle real-world limitations Build scalable and maintainable AI applications For more detailed information on the progress of this course, you can check the introductory video and free lessons, and if you decide to enroll in this course, you are always welcome to ask and discuss the concepts and implementation details on Q/A and messages sections. I will guide you from start to finish to help you successfully complete the course and gain as much knowledge and experience as possible from this course. Support & updates You can ask questions anytime in Q&A The course will be continuously updated as Spring AI evolves You’ll get guidance to fully understand and apply concepts Remember! There is a 30-day full money-back guarantee for this course! So you can safely press the 'Buy this course' button with zero risk and join this learning journey with me.