• views: 94
• date: 24 September 2025
• posted by: 0nelove

What you'll learn
Generative AI foundations
Use of LLM models in spring boot applications
OpenAI Chat model integration using spring boot
Multimodality - Image & Audio models
RAG - Retrieval Augmented Generation
Requirements
Need to know java programming
Spring boot basics
maven build tool
IntelliJ editor
Description
Master Generative AI using Spring Boot is your complete guide to building powerful, production-ready AI applications using Java and the Spring Boot framework. In this hands-on course, you'll learn how to integrate cutting-edge generative AI models—such as OpenAI's GPT for chat, Image models like Dall-e, Audio models and custom LLMs—directly into scalable backend services.Whether you are developing chatbots, AI-powered recommendation engines, or intelligent document summarizers, this course will show you how to bridge the gap between generative AI capabilities and enterprise-grade software development. What You'll LearnThe fundamentals of generative AI and LLMs (large language models)How to work with APIs like OpenAI - Chat, Image and AudioCreating secure and scalable REST APIs using Spring BootStoring and querying vector embeddings using vector databases (e.g., Postgres Vector Database)Using prompt engineering and retrieval-augmented generation (RAG) Who This Course is ForJava/Spring developers curious about integrating AIBackend engineers looking to expand into AI application developmentSoftware architects building intelligent microservicesTech enthusiasts wanting real-world AI project experienceKey Skills You'll Gain:Generative AI fundamentals and APIs (OpenAI Chat, Image and Audio)Spring Boot for backend service developmentEmbedding and vector database integration (FAISS, Qdrant, etc.)Prompt engineering and RAG techniquesNo prior AI/ML background required—this course bridges the world of traditional backend development and modern generative AI, one step at a time.
Who are interested to get started with their journey to learn Generative AI using spring boot,What is LLM and how they work,Use of different models like chat, Image and Audio in spring boot applications,RAG - Retrieval Augmented Generation and its use case
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