AI for Java Developers: Full Course / Workshop on Getting Started with Spring AI

*Every Java Developer is now an AI Developer. Transform your Java skills for the AI era with this comprehensive 5.5-hour Spring AI masterclass!* Are you a Java developer ready to harness the power of AI in your applications? This complete course takes you from AI fundamentals to building production-ready intelligent applications using Spring AI 1.0. 🎥 Video Timestamps Introduction & Setup *00:00* - Course Introduction & What We'll Build *08:45* - Getting Started: API Keys & Project Setup *18:30* - Your First AI Application with Spring AI AI Fundamentals *28:15* - What is AI? Machine Learning & Deep Learning Explained *35:20* - Large Language Models & Transformers *42:10* - Prompt Engineering Fundamentals *52:30* - Why Java & AI? Spring AI Overview Spring AI Core Features *1:02:45* - Chat Clients & Streaming Responses *1:15:20* - Prompts & System Messages *1:28:40* - Structured Output with Type Safety *1:42:15* - Multimodal AI: Images & Audio Processing *1:58:30* - Chat Memory & Conversation State Overcoming LLM Limitations *2:12:20* - Understanding LLM Limitations *2:18:45* - Prompt Guarding & Security *2:25:10* - Prompt Stuffing & Context Enhancement *2:32:30* - Retrieval Augmented Generation (RAG) *2:52:15* - Tools & Function Calling *3:15:40* - Model Context Protocol (MCP) Servers Open Source Models *3:45:20* - Open Source vs Proprietary Models *3:52:30* - Running Local Models with Ollama *4:02:15* - Docker Model Runner & LM Studio *4:10:45* - Using Local Models in Spring AI Production & Monitoring *4:18:30* - Observability with Prometheus & Grafana *4:32:20* - Metrics That Matter for AI Applications *4:41:15* - Testing AI Applications & Model Evaluations *4:56:30* - Deterministic vs Non-Deterministic Testing Conclusion & Next Steps *5:08:45* - Key Takeaways & Best Practices *5:15:20* - Resources & Community *5:22:30* - Building Your AI Portfolio *5:30:15* - What's Next & Course Wrap-up 🎯 *What You'll Master:* *Foundation & Theory* AI fundamentals: Machine Learning, Deep Learning, and LLM architecture Prompt engineering mastery - the most critical skill for AI developers Model selection strategies and cost optimization with tokens *Spring AI Implementation* Chat clients with streaming responses and memory management Structured outputs and multimodal processing (images, audio) Multiple AI model integration in single applications Prompt templates and advanced configuration *Overcoming LLM Limitations* Retrieval Augmented Generation (RAG) for enhanced accuracy Custom tool development and function calling Model Context Protocol (MCP) for reusable integrations Prompt guarding and security best practices *Production Excellence* Open-source vs proprietary model comparison Running local models with Ollama and Docker Observability with Prometheus and Grafana Testing strategies for non-deterministic AI systems 🛠 *Hands-On Workshop:* Build intelligent chatbots with conversation memory Create document analysis systems using RAG Develop custom AI tools and MCP servers Implement multimodal applications processing text, images, and audio 💡 *Perfect For:* Java developers entering the AI space Spring Framework users wanting AI capabilities Developers building chatbots and intelligent features Anyone seeking practical AI implementation without ML theory 📋 *Prerequisites:* Basic Java knowledge Familiarity with Spring Framework No machine learning background required! *🚀 Ready to become an AI-powered Java developer?* This course provides everything you need to build intelligent applications that users love and businesses need. *📚 Resources:* Complete source code on GitHub *🔥 Transform your development career - Start building AI applications today!* 👋🏻Connect with me: Website: https://www.danvega.dev Twitter:   / therealdanvega   Github: https://github.com/danvega LinkedIn:   / danvega   Newsletter: https://www.danvega.dev/newsletter SUBSCRIBE TO MY CHANNEL: http://bit.ly/2re4GH0 ❤️