From the basics of the latest Spring AI to MCP
I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.
148 learners
Level Basic
Course period Unlimited
Spring AI Multi-LLM Architecture and Orchestration-focused Agent System Course - Scheduled for Upgrade
Hello, I am Jinman Lee (tootoo), your knowledge sharer.
Spring AI Multi-LLM Architecture and Orchestration-focused Agent System
I am sharing news regarding an upgrade to the course.
The upgrade is scheduled for mid-April, and it will be released with the following structure.
For those who have already purchased, please watch up to Chapter 3 and then continue from Chapter 4 onwards.
The price of this course is scheduled to increase slightly starting in mid-April, so it might be a good idea to purchase it in advance.
Thank you.
The overall course materials have been revised, and while Chapters 1 through 3 focused primarily on studying Patterns,
Chapters 4 through 8 are composed of the process of creating practice-oriented Multi-Agents.
Chapter 1. Multi-LLM Architecture (Multi-Model Strategies and Enterprise AI Architecture Design)
Chapter 2. Agentic Workflow Patterns (5 Agent Workflow Patterns Used in Practice)
Chapter 3. Orchestrated Multi-Agent Patterns (Implementing Multi-Agent Structures into Actual Service Pipelines)
Chapter 4. Multi-Agent Architecture (SubAgent Separation Strategy and Agent Registry Internal Structure)
Chapter 5. Tool-Orchestrated Multi-Agent (Architecture for Separating Execution Layers Using Tools)
Chapter 6. Task-Orchestrated Multi-Agent (Designing Agent Runtime based on TaskTool)
Chapter 7. DAG-Orchestrated Multi-Agent (Enterprise-grade DAG-based AI Workflow Design)
Chapter 8. Declarative Agent Workflow with YAML (Separating YAML-based DAG Definition and Execution Engine)