Building Generative AI Applications with Java and Spring

As generative artificial intelligence transforms the software landscape, Java developers need practical ways to integrate intelligent features into their existing application ecosystems. This course bridges the gap between enterprise Java development and modern AI capabilities using the robust Spring framework. You will transition from standard backend development to building smart, context-aware applications. By understanding the foundational concepts of machine learning and large language models, you will learn how to safely and efficiently connect your Spring Boot services to external AI APIs, manage prompts, and handle unstructured data. What you'll learn: - Understand the core terminology of generative AI, neural networks, and large language models. - Configure Spring applications to securely connect with top-tier AI services and APIs. - Implement Retrieval-Augmented Generation (RAG) patterns to ground AI responses in your own data. - Apply prompt engineering techniques directly inside Java code to guide model outputs. - Manage unstructured data using vector databases integrated into your Spring services. - Practice writing clean, modern Java code to parse, structure, and validate AI-generated responses. The curriculum starts with essential definitions and foundational AI concepts before guiding you through structured written tutorials and code-based exercises. You will progress from simple text generation to building advanced, retrieval-augmented application flows. This course is designed for Java developers who are new to artificial intelligence and want to expand their backend skills without needing a background in data science. Start reading today to bring the power of generative AI to your Java and Spring applications.