Generative AI Development with Java and Spring

As artificial intelligence transforms the software landscape, Java developers need practical skills to integrate intelligent features into enterprise systems. This course bridges the gap between traditional backend development and modern AI engineering. You will transition from writing standard backend services to building intelligent, context-aware Java applications. By understanding the core mechanics of large language models and leveraging modern Spring ecosystem tools, you will confidently design systems that process natural language, manage prompt templates, and connect to external data sources. What you'll learn: - Understand foundational generative AI concepts, large language models, and tokenization from a developer's perspective - Configure Spring AI to connect your Java applications securely to leading AI models - Apply prompt engineering techniques programmatically using structured templates and output parsers - Implement Retrieval-Augmented Generation (RAG) using vector databases to ground AI responses in your private data - Manage chat memory and conversational state in Spring-based web applications - Practice writing clean, modern Java code to parse, process, and secure AI-driven interactions The course starts with essential AI terminology and foundational concepts before moving into configuration and implementation. You will read through step-by-step explanations and analyze practical code snippets that demonstrate how to connect Spring Boot services to vector stores and model providers. This course is designed for Java and Spring Boot developers who want to enter the AI space. No prior background in machine learning or data science is required. Start reading today to adapt your Java expertise for the era of artificial intelligence.