If you’re looking for a clear, no-nonsense path into generative AI on Java, this series is for you.  Microsoft’s Java and AI for Beginners video series is a set of short tutorials that introduce the concepts, tooling, and patterns you need to get started at a pace that respects your time and experience.

What the series covers

We help you through foundational ideas first and then move into hands-on examples:

• Getting started fast – Spin up your first AI-powered app using GitHub Codespaces.

• Core generative AI techniques – Learn the basics behind completions and chat flows. See how function calling connects models to real tools and services. Get an introduction to Retrieval-Augmented Generation (RAG) for document-aware applications.

• Simple, focused application – Explore small projects that illustrate different capabilities, such as combining text and image generation, running models locally with the Azure AI Foundry Local experience, and wiring tools with the Model Context Protocol (MCP).

• Responsible AI – Apply safety features from GitHub Models and Azure services. We cover content filtering, bias awareness, and practical checks you can add before deployment.

• MCP in Java – Understand the Model Context Protocol and how it fits Java workflows. Learn what it means to implement an MCP server, connect a Java client, and use tools through a consistent protocol.

• Context engineering for Java – Improve results with clean prompts, structured context, and simple evaluation steps. We discuss when to persist context and when to compute it on the fly.

• Modernization with AI assistance – See how the GitHub Copilot App Modernization experience helps upgrade and migrate Java applications. Then follow a guided flow to deploy to Azure with AI-assisted configuration.

• LangChain4j essentials – Start a basic project that targets OpenAI-compatible endpoints, then build a small agent with tools and memory to understand the moving parts.

• Running GenAI in containers – Review when to use on-demand GPUs for inference and training. Learn how dynamic sessions in Azure Container Apps support code interpreters and short-lived, cost-aware execution.

Each video is short and focused. Watch them in order if you are new to the space, or skip into the topics that match your immediate needs.

Integrations you will see

The series uses services and libraries that many Java teams already rely on:

• OpenAI and GitHub Models

• LangChain4j for building Java-based AI applications with open-source patterns

• Model Context Protocol to connect tools and services through a common protocol

Where it helps, we use the official OpenAI Java SDK to target both OpenAI and Azure OpenAI endpoints with consistent code paths and Azure-aware authentication and security options.

Microsoft’s investment and community partnership

This series reflects ongoing work with the Java open-source community. The Microsoft Java advocacy and engineering teams continue to contribute to projects like LangChain4j and Spring AI, improve Azure and OpenAI integrations, and provide open-source examples that run locally and on the cloud. Your feedback from conferences, meetups, issue threads, and customer projects shaped each of the outlines for these videos.

Get started

The playlist, code links, and references are available on the Microsoft Developer YouTube channel :

https://aka.ms/java-ai-beginners

Also subscribe to the Microsoft for Java Developers YouTube Channel

If you have suggestions or want a deeper dive on a specific area, let me know—your input will guide future installments.