Generative AI for Beginners - Java Edition

4:00 p. m. - 5:00 p. m. (UTC)

Learn the fundamentals of integrating generative AI into Java applications. We'll cover Large Language Models, tokens, embeddings, and set up your development environment. Build your first AI-powered application with hands-on exercises using GitHub Codespaces—no local setup required. You'll learn: LLM concepts GitHub Models and Azure OpenAI setup Spring AI integration patterns Building your first AI Java application

4:00 p. m. - 5:00 p. m. (UTC)

Explore the fundamental techniques that power AI applications. This session covers completions and chat flows, function calling to connect AI with external tools, Retrieval-Augmented Generation (RAG) for document-based AI, and responsible AI safety measures. Through hands-on examples you'll learn to implement these patterns in production Java applications. You'll Learn: Streaming completions and conversation management Function calling with JSON schemas RAG pattern for document Q&A Content filtering and safety handling

4:00 p. m. - 5:00 p. m. (UTC)

Lets build three working applications that demonstrate different AI capabilities. Create a Pet Story Generator that generates text and images together, implement offline AI with Foundry Local, and build a Calculator Service using Model Context Protocol (MCP) for tool integration. You'll Learn: Combining text and image generation Running AI models locally vs cloud Tool integration with MCP

4:00 p. m. - 5:00 p. m. (UTC)

Implement responsible AI practices in Java applications. Using GitHub Models' and Azure's safety features, learn content filtering, bias detection, and Microsoft's Responsible AI principles. Essential session for deploying trustworthy AI solutions in production environments. You'll Learn: Content filtering and safety testing Responsible AI implementation patterns Production deployment guidelines Compliance and governance practices