
Before installing OpenClaw, you need a proper environment. In this lecture, you’ll learn how to create a Linux virtual machine using Google Cloud Compute Engine. We’ll configure a cost-effective server with the right specifications so your AI agent runs smoothly.
What you’ll learn:
Creating a Linux VM from scratch
Choosing machine size and region
Preparing cloud infrastructure for AI agent deployment
Now that your server is ready, it’s time to connect securely. In this lecture, you’ll generate SSH keys and establish a secure remote connection from your local machine to your cloud server. This setup allows you to manage and install OpenClaw directly from your terminal.
What you’ll learn:
Generate SSH keys on Windows/Linux
Configure cloud metadata access
Connect securely to your remote machine
In this hands-on lecture, you’ll prepare your Linux environment for OpenClaw installation. We’ll update the system, install required tools, configure users with proper permissions, install Node.js, and finally deploy OpenClaw from source.
What you’ll learn:
System updates and essential package installation
Creating secure users with sudo access
Installing Node.js and OpenClaw step-by-step
After installation, we’ll go through the OpenClaw onboarding wizard. You’ll connect your AI model using API keys, choose the right model, and integrate OpenClaw with WhatsApp so you can interact with your AI assistant from your phone.
What you’ll learn:
Secure onboarding process
Adding OpenAI API keys
Connecting messaging platforms like WhatsApp
Understanding onboarding security warnings
In this lecture, you’ll learn how to launch and control OpenClaw using the Terminal UI. We’ll configure gateway services, troubleshoot common issues, and start your first AI interaction. You’ll also see how OpenClaw processes prompts and manages tokens behind the scenes.
What you’ll learn:
Starting OpenClaw services and gateway
Using Terminal UI for interaction
Running your first AI conversation
This practical lecture demonstrates the real power of OpenClaw automation. You’ll see how the AI agent can create files, schedule recurring tasks, read workspace data, and even summarize content from websites. This is where OpenClaw starts behaving like a true autonomous assistant.
What you’ll learn:
Automating file creation with AI
Scheduling background jobs
Reading and modifying workspace files
Web browsing and summarization tasks
AI agents are transforming how we build automation, intelligent assistants, and developer tools.
OpenClaw is one of the most powerful open-source AI agent frameworks that allows you to build intelligent systems capable of performing real tasks using tools, skills, and automation workflows.
In this course, you will learn how OpenClaw works, how to install it, and how to run your own AI agent environment.
We start with the fundamentals of OpenClaw, including its architecture, built-in tools, and bundled skills that power AI automation.
You will then learn multiple ways to install OpenClaw, so you can choose the setup that works best for your environment.
The course covers:
One-click OpenClaw cloud deployment
Local installation on Windows
Ubuntu installation using Windows WSL
Optional Google Cloud VM deployment
Once OpenClaw is installed, we explore the platform in depth, including:
OpenClaw onboarding
User interface exploration
Terminal User Interface (TUI)
Configuration using openclaw.json
Documentation walkthrough
Troubleshooting installation issues
You will also learn how to run AI agents, automate tasks, and perform real operations like file creation, scheduling jobs, and web summarization.
By the end of this course, you will be able to:
Install OpenClaw in different environments
Configure OpenClaw with API keys and settings
Understand OpenClaw tools and skills
Run and interact with AI agents
Deploy OpenClaw in local or cloud environments
If you want to learn how modern AI agents work and start building with OpenClaw, this course will give you the complete foundation.