Master AI Agents: From Basics to Advanced Multi-Model Development
This comprehensive AI agent development course covers 18 chapters, ranging from fundamental concepts and architecture to large‑model integration, tool and browser control, memory, RAG self‑learning, sandboxing, database manipulation, multi‑agent architectures, code assistance, and a real‑world frontend automation project, complete with source code and documentation.
Chapter 1: Course Introduction
Chapter 2: Essential Concepts and Technical Architecture of AI Agents
Chapter 3: Large Model Invocation in AI Agent Development (LLM capabilities)
Chapter 4: LangChain Tool Development for AI Agents (Agent tool capabilities)
Chapter 5: Built-in Tool Invocation and Response Control (Agent integration capabilities)
Chapter 6: Deep Dive into MCP Protocol (External tool capabilities of AI Agents)
Chapter 7: Cursor + MCP Integration (Intelligent tools for AI Agents)
Chapter 8: Project Planning and Multi‑turn Dialogue Implementation for AI Programming Agents
Chapter 9: Memory Capability Implementation for AI Programming Agents
Chapter 10: Terminal Control Tool Development for AI Programming Agents
Chapter 11: Knowledge Base Development for AI Programming Agents
Chapter 12: RAG Self‑Learning Mechanism for AI Agents
Chapter 13: Browser Control Development for AI Agents
Chapter 14: Implementing an Agent Sandbox (Sandbox execution capability)
Chapter 15: Database Tool Development for AI Agents (Database manipulation capability)
Chapter 16: LangGraph Multi‑Agent Architecture (Architectural capability)
Chapter 17: Code Assistance Development for AI Agents (Programming assistance capability)
Chapter 18: Real‑World Project Deployment: Front‑end Page Automation for XiaoMu Bookstore (Frontend project practice)
Course source code and documentation are provided.
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