Perfect Understanding and Practical Implementation of AI Agents: From Multi-Agent to Kubernetes Automation

This is a practical, hands-on course where you will learn the principles of AI Agents—going beyond simple chatbots that just answer questions to systems that can perceive situations, make judgments, and control actual systems. The curriculum is structured to provide a step-by-step understanding, starting from the differences between AI Agents and chatbots to the core Agent Loop structure: Sense-Think-Act, state management, planning, and feedback loops. Moving beyond theory, you will set up Windows and Linux development environments and gain hands-on experience with the basic structure of Kubernetes and kubectl commands. Following this, you will implement a process where an AI Agent detects server issues, analyzes the causes, and automatically resolves errors. Finally, by directly analyzing the Python code and internal logic of the Agent controlling Kubernetes, you will understand how AI Agents connect to and operate within real-world systems. From developers new to AI Agents to those who want to design Multi-Agents that control actual systems, this course allows you to learn both the principles and the practical implementation process of Agents.