[UDM] Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026) Course (Dec 2025) + Files

Build Real AI Apps Using Java and Spring
Explore the potential of creating simple AI applications with Java and the Spring Framework. The Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026) Course is ideal when developers wish to incorporate AI functionalities in their Spring Boot projects to add chatbots, document search, and image generation, but they do not have to be AI experts. You will begin with the fundamentals of the working of large language models (LLMs) and continue to develop production-ready AI functionality with help for the applications of the day.

Learn LLMs, Prompt Engineering & Multimodal AI
The Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026) Course starts with key principles: prompts work, token limits, and the influence context has on AI outputs. It is there that you will be immersed in the field of working with different AI modalities, not only text, but also audio, speech, and images. You will also have the opportunity to send prompts to OpenAI or local models and process the responses programmatically with Spring AI with the help of hands-on labs. It will be summarization, translation, and image generation, but all of that will be implemented in Spring-based Java.

Create Smart Chatbots & RAG Systems
Go beyond simple chatbots and develop advanced agents that can call tools and Retrieval-Augmented Generation (RAG) pipelines. You will get to know how to chunk documents, create embeddings, and store them in a vector database (such as PgVector) and run semantic search, which will retrieve contextual information. This is the basis of the modern knowledge assistants and AI tools that are much more than simple Q&A bots.

Build Full-Stack AI Products with Spring + React
In the last project of the Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026) Course, you will create a complete full-stack AI application, such as a company HR chatbot, with a Spring Boot backend, an administrator dashboard, chat history memory support, and a React frontend. This capstone project will show how one can develop scalable AI applications that are not just functional but also user-friendly, which are enterprise-ready. At the end, you will have a complete deployable product to include in your portfolio or even apply in production.