Building AI Systems with Spring AI
Certificate of Completion by Code.Hub
“Building AI Systems with Spring AI” is a comprehensive course that teaches developers how to design and implement production-ready AI-powered applications using the Spring AI framework. The course covers the full spectrum of modern AI development, from understanding core architectural concepts and prompt engineering to building conversational agents with memory, integrating retrieval-augmented generation (RAG) pipelines, leveraging tool calling and MCP, and deploying both cloud-based and offline language models.
By the end of this module, participants will be able to:
- Architect and build AI-powered services using Spring AI within a familiar Java/Spring ecosystem
- Write effective prompts using templates, few-shot examples, and structured output techniques
- Design stateful conversational applications with appropriate memory strategies
- Implement RAG pipelines to ground LLM responses in real data and reduce hallucinations
- Integrate external tools and MCP servers into multi-step AI workflows
- Deploy and switch between cloud-hosted and locally running language models using Docker
Spring AI Core Concepts
AI vs traditional services
Spring AI architecture
ChatClient
Models/messages
System vs user instructions
Prompt Engineering
Prompt templates
Instruction vs context
Few-shot prompting
Structured outputs
Conversational AI & Memory
Stateless vs stateful conversations
Memory patterns (sliding window, summary, store-backed)
Memory lifecycle
RAG Foundations & Basic Monitoring
LLM hallucinations
RAG pipeline overview
query→retrieval→context→generation
Chunking strategies
Logging
Token usage monitoring
Tool Calling & MCP
Tools vs APIs
Validation
Error handling
Multi-step flows
MCP client/server basics
Offline & Hybrid LLM Deployment
Cloud vs offline models
Model selection & quantization
Docker deployment
Switching between cloud/local
- Roles: Backend Engineers, Software Architects, Technical Leads, Solution Architects
- Seniority: Mid-Level to Senior Professionals
- Solid understanding of Java and the Spring Framework (Spring Boot experience is strongly recommended)
- Familiarity with REST APIs and basic software architecture patterns
- Basic understanding of what Large Language Models (LLMs) are and how they are used
- Experience with Docker is helpful, particularly for the offline deployment module
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
Interested for

