What You'll Learn
A practical Spring AI program for Java developers who want to build enterprise-ready AI applications. The course covers integrating large language models into Spring Boot services, prompt engineering, retrieval-augmented generation, vector search, and designing maintainable AI-enabled backend systems.
Curriculum Highlights
- Introduction to Spring AI and the Java ecosystem for generative AI applications
- Connecting Spring Boot applications to LLM providers and AI model APIs
- Prompt templates, prompt composition, and structured output handling
- Chat models, completion workflows, embeddings, and model abstraction layers
- Retrieval-Augmented Generation (RAG) architecture and knowledge-based assistants
- Working with vector databases and semantic search in Spring applications
- Designing AI-enabled REST APIs with Spring Boot
- Document ingestion pipelines for PDFs, markdown, and enterprise knowledge sources
- Context management, memory, and conversation flow design
- Guardrails, validation, fallback handling, and responsible AI patterns
- Observability, cost awareness, prompt evaluation, and production considerations
- Real-world project: build a Spring AI assistant service with retrieval, prompts, and API integration
Who Is This For
Java and Spring Boot developers, backend engineers, and solution architects who want to add LLM capabilities to enterprise applications using modern Spring-based patterns.
Format
Delivered as 30 hours of live interactive training with coding walkthroughs, guided exercises, and project-based implementation. Available as a corporate cohort or 1-on-1 mentorship program.