OpenClaw 联动 Claude：多智能体 AI 系统构建进阶课程

零基础搭建全栈AI操作系统实战训练营

本次OpenClaw + Claude + Clawdbot人工智能操作系统实战训练营，面向零基础人群开设，仅要求学员具备基础编程认知、熟悉网页与API操作及稳定上网条件，无需AI和机器学习前置经验；课程将分步教学，先讲解智能主体AI基础原理，再带领学员深耕智能体搭建、多智能体协同编排、记忆驱动型AI系统开发等核心内容，同时教授工具调用、自动化流程搭建、长效自主系统部署及AI性能优化技巧，学员还可通过个人AI操作系统、商业自动化流程、自主研究智能体等高价值结业项目实战落地所学，完成学习后，学员能够具备专业AI架构师能力，独立设计、搭建并部署商业化落地的完整人工智能系统。

课程时长：4小时 1920X1080 mp4 语言：英语 含课程文件

AI Operating System Bootcamp: OpenClaw + Claude + Clawdbot

Build a full AI OS using Claude, multi-agent systems, memory, and automation with real-world projects

“This course contains the use of artificial intelligence”

Are you ready to go beyond using AI tools and start building complete AI systems?

This course is your step-by-step guide to designing and building a full AI Operating System using Claude, multi-agent architectures, memory systems, and automation pipelines. Instead of learning isolated tools, you will learn how to combine them into scalable, real-world systems.

You will start by understanding the foundations of Agentic AI, including how modern systems evolve from simple prompts to intelligent, autonomous workflows. Then, you’ll dive deep into building intelligent agents, designing multi-step reasoning systems, and implementing multi-agent orchestration.

One of the most powerful aspects of this course is learning how to build memory-driven AI systems, enabling your agents to retain context, learn from interactions, and make better decisions over time. You will also learn how to connect AI with real-world tools through function calling, APIs, and automation pipelines.

As you progress, you will build long-running autonomous systems, implement feedback loops, and optimize performance for cost, latency, and scalability.

Finally, you’ll apply everything through high-value capstone projects, including

• A personal AI operating system

• A business automation pipeline

• An autonomous research agent

By the end of this course, you won’t just understand AI — you’ll be able to design, build, and deploy real-world AI systems like an AI Architect.

What you’ll learn
Build a complete AI Operating System by combining agents, memory, and automation into one unified system
Design and deploy intelligent AI agents using structured prompts, reasoning, and multi-step workflows
Create and manage multi-agent systems with supervisor-worker architectures and task orchestration
Implement memory-driven AI systems using vector databases, embeddings, and context injection techniques
Develop tool-calling and automation pipelines to connect AI with real-world APIs, workflows, and data systems
Build long-running autonomous AI systems with event-driven execution, scheduling, and feedback loops
Optimize AI systems for performance, cost, and scalability including token efficiency and latency reduction
Apply skills through real-world projects like personal AI assistants, business automation systems, and research agents

Requirements
Basic understanding of programming concepts (Python or JavaScript is helpful but not mandatory)
Familiarity with using web applications and APIs is a plus, but everything will be explained step-by-step
No prior experience in AI or machine learning is required — this course starts from fundamentals
A computer or laptop with a stable internet connection
Willingness to learn by building real-world projects and experimenting with AI systems