| File Name: | Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026) |
| Content Source: | https://www.udemy.com/course/spring-ai-build-java-ai-apps-chatbots-rag-systems-2026 |
| Genre / Category: | Programming |
| File Size : | 4.3 GB |
| Publisher: | udemy |
| Updated and Published: | December 2, 2025 |
The AI revolution is here, and enterprise systems are still powered by Java. Java developers need a modern, practical way to integrate LLMs without deep data science knowledge. This course is the direct answer, transforming you from a Spring Boot developer into a high-demand AI engineer. We cut through the noise and show you exactly how to build robust, scalable AI features using the familiar patterns of the Spring ecosystem.
We move quickly from foundational concepts to hands-on, production-ready features.
- Foundations (Module 1): Master the core mechanics of LLMs—tokens, prompts, and context windows—which are the building blocks of every AI application.
- Core Integration (Module 2-3): Build your first Spring AI application from scratch. Go beyond text generation to integrate image generation , Text-to-Speech (TTS) , Speech-to-Text (STT) , and multimodal (vision/audio) capabilities. You’ll implement moderation pipelines using both OpenAI and the free Mistral model.
- The Power of Local AI (Module 4): Free yourself from cloud costs and latency. Learn how to install and use Ollama to run fast, local models like Gemma directly on your machine. We implement real-time streaming using Spring WebFlux and even integrate local Whisper Api via Docker.
- Intelligent Agents (Module 5): Build AI agents that take actions. Master Tool Calling (Function Calling) to let the LLM securely trigger your Spring Boot business logic, fetch real-time data (like weather) , and orchestrate complex workflows.
- RAG Mastery (Module 6-7): The most critical enterprise skill. We start by building a custom RAG pipeline from scratch using embeddings and cosine similarity. Then, we integrate fully with PgVector—the gold standard for RAG—to implement scalable semantic search, document ingestion (PDF chunking via Tika), and lifecycle management.
- The Capstone Project (Module 8): Bring it all together by building a Full-Stack HR Assistant Chatbot. This project features:
- Admin APIs for knowledge base management.
- Spring AI Chat Memory for personalized conversations.
- A full conversation management API.
- A complete, AI-generated React Frontend.
By the end of this course, you will have the confidence and portfolio to build real, feature-rich, AI-powered applications that solve genuine business problems.
DOWNLOAD LINK: Spring AI: Build Java AI Apps, Chatbots & RAG Systems (2026)
Spring_AI_Build_Java_AI_Apps_Chatbots_RAG_Systems_2026_.part1.rar – 1000.0 MB
Spring_AI_Build_Java_AI_Apps_Chatbots_RAG_Systems_2026_.part2.rar – 1000.0 MB
Spring_AI_Build_Java_AI_Apps_Chatbots_RAG_Systems_2026_.part3.rar – 1000.0 MB
Spring_AI_Build_Java_AI_Apps_Chatbots_RAG_Systems_2026_.part4.rar – 1000.0 MB
Spring_AI_Build_Java_AI_Apps_Chatbots_RAG_Systems_2026_.part5.rar – 359.8 MB
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