Learn OpenClaw, the viral open-source autonomous AI agent. Understand the Gateway architecture, install and configure your own agent, master skills and memory, secure your setup with Docker sandboxing, build multi-agent teams, publish skills to ClawHub, and optimize performance.
OpenClaw is an open-source autonomous AI agent that has gained rapid attention for letting anyone deploy, customize, and coordinate AI-powered workflows without writing extensive code. This free course walks you through everything from the first installation to running multi-agent teams, so you can put autonomous AI to work in your own projects, studies, or professional tasks.
You will start by understanding what OpenClaw actually is and how its Gateway architecture routes tasks between your agent and the tools it uses. From there you will install and configure your own local instance, then explore Skills and Memory so your agent can learn context and take repeatable actions. The course also covers Docker sandboxing to keep your setup secure, and it shows you how to build your own Skills and publish them to ClawHub so others can benefit from your work.
The final module moves into practical workflows: designing your first automated sequences, setting up multi-agent collaboration where several specialized agents work together, and diagnosing performance bottlenecks when things go wrong. No prior experience with autonomous agents is required, just a willingness to experiment. The course is completely free, and passing the final exam earns you a certificate of completion you can add to your LinkedIn profile or resume.
3 modules • 9 lessons
Finish every lesson and pass the final exam to earn this free, shareable certificate.
Verify
June 15, 2026
This certifies that
has successfully completed the course
Sample preview. Your name appears on the certificate when you complete the course. Learn more
OpenClaw is an open-source autonomous AI agent framework that lets you automate complex tasks by chaining Skills, maintaining Memory, and coordinating multiple agents. It has attracted a large community because it gives learners and professionals a hands-on path into real agentic AI without vendor lock-in.
Yes, the course is completely free and requires no signup to start. You can work through all three modules, covering fundamentals, security, and advanced workflows, at your own pace.
No prior autonomous-agent or advanced programming experience is needed. The course is designed for beginners and introduces each concept, from installation to multi-agent collaboration, step by step.
The course covers the OpenClaw Gateway architecture, local installation and configuration, Skills and Memory management, Docker-based sandboxing for security, building and publishing Skills to ClawHub, designing workflows, setting up multi-agent teams, and troubleshooting performance.
Yes. Finishing all the lessons and passing the final exam earns you a certificate of completion that you can share on LinkedIn or include on your resume to show practical knowledge of autonomous AI agents.
Go beyond basic prompts and master professional AI image generation. Learn Midjourney parameters and styles, DALL-E 3 techniques via ChatGPT, advanced prompting with weights and negative prompts, consistent character generation, AI inpainting, and real-world workflows for social media and marketing assets.
Master Google Gemini from scratch. Learn what Gemini is, set up your account, discover its unique strengths, write effective prompts, use Gemini across Google Workspace, compare it with ChatGPT and Claude, and build advanced real-world workflows.
Master Perplexity AI for accurate, sourced research. Learn effective query writing, understand sources and citations, use Pro Search features, and develop academic research workflows. Perfect for researchers, students, journalists, and anyone who needs fact-checked information.
Move beyond chatbots. Build autonomous agents that work for business. Learn to create production-ready AI agents using JavaScript, TypeScript, Next.js, and the Vercel AI SDK. Perfect for JavaScript developers who want to build AI applications without learning Python.
Master the probabilistic foundations of artificial intelligence. Learn probability fundamentals, Bayes' theorem, distributions, expected value, maximum likelihood estimation, and how AI systems handle uncertainty to make predictions.
Master the principles, architecture, and core components required to build production-ready RAG applications. Learn to create custom knowledge chatbots using Next.js, Supabase with pgvector, and Google's Gemini API. Perfect for JavaScript/Next.js developers who want to integrate advanced AI features.
