Microsoft Latest AI Agent Intro Course is a practical course on AI agent systems for beginners. Starting from what is an AI Agent, it gradually explains the core components of intelligent agents such as large language models, tools, memory, and planning. Combined with Microsoft Semantic Kernel and large model code examples, it helps learners understand how AI Agents identify user tasks, formulate execution plans, call external tools, and use contextual memory to complete tasks. The course further covers AI agent framework selection, Agent design methods, tool calling design patterns, agentic RAG, planning patterns, multi-AI agent collaboration, context engineering, and long-term memory and self-improvement mechanisms, helping learners build a complete Agent development mindset. It also explains how to truly deploy AI agents from experimental environments to production environments, as well as the practical roles of agent protocols such as MCP, A2A, and NLWeb.

This course is taught entirely in English with no subtitles, suitable for learners with some English foundation. Through complete learning from concepts and architecture to code and deployment, you will not only understand the construction logic of AI Agents, but also master the key steps of intelligent agents from design to launch, laying a solid foundation for developing intelligent assistants, automated workflows, knowledge base Agents, and multi-agent applications. Whether you are a beginner hoping to enter the AI field or an engineer wanting to systematically improve Agent development capabilities, this course provides a clear path and practical methods.

\
• 1.导学
\
• 2.Which AI agent framework to use
\

\
• 3.How to design good AI agents
\
• 4.What is the agent tool use design pattern
\
• 5.What is agentic RAG
\

\
• 6.How to build effective AI agents
\
• 7.What is the AI agent planning design pattern
\

\
• 8.How to use multi-AI agent systems
\
• 9.How AI agents improve
\
• 10.Context engineering for AI agents
\
• 11.AI agent memory: building self-improving agents
\

\
• 12.How to deploy AI agents to production
\
• 13.Using agent protocols (MCP, A2A, and NLWeb)
\

💡 Learning Tip:Content reflects industry practices at time of publication. Please refer to the latest platform rules when learning.