
Build a real autonomous AI agent with OpenClaw and NemoClaw from a blank server to a secure, always-on system connected to your chosen LLM, tested on real infrastructure.
Meet OpenClaw, a 24x7 open source ai agent. Runs on macos, linux, windows, with eyes and hands to browse the web, read and write files, and execute code autonomously.
OpenCLO is a self-hosted, open-source, provider-agnostic autonomous agent that browses, reads, writes, and initiates tasks, contrasting with chatgpt's reactive interface and cloud code's closed, model-locked setup.
Explore the OpenCLO architecture, turning VPS into a secure, always-on AI agent reachable through an SSH tunnel or VS Code port forwarding, with dedicated non-root user and localhost gateway.
Set up a DigitalOcean account, generate an ed25519 SSH key pair, add the public key to DigitalOcean, and prepare a passwordless VM (droplet) for OpenClaw development.
Set up a Ubuntu 24.04 LTS vps on DigitalOcean by creating a droplet, configuring ssh key authentication, and connecting via ssh for a 24x7 OpenCLO agent server.
Generate a Moonshot API key, load credit, and create a dedicated OpenCLO agent user on the VPS with SSH access, using Kimi K2.5 and a fallback model.
Create a non-root user for OpenCLO, assign sudo for package installs, enable a systemd user service with linger, and configure passwordless ssh access for the OpenCLO agent.
Install node.js 24 from the Node source repo on Ubuntu, then securely store the Moonshot API key by creating a restricted secrets file, setting 600 permissions, and updating .bashrc.
Verify the full OpenCLO stack end-to-end, troubleshoot with health checks and logs, and enable AI-assisted debugging using the TUI and Brave web search tests.
Access the web dashboard securely by tunneling local port 18789 to the gateway on 127.0.0.1 via ssh, keeping the ui private and requiring a token from openclaw.json.
Learn to install the VS Code remote SSH extension, connect to the OpenCloudVPS, configure the ssh config, and edit the VPS file system directly from VS Code.
Learn a daily VS Code remote SSH workflow to manage the OpenClaw gateway, edit openclaw.json, monitor logs with journalctl, and use port forwarding to access the dashboard from localhost.
Connect your OpenCLO agent to Telegram using BotFather, create a bot, obtain the API token, and secure it on your VPS to enable seamless, multi-channel AI conversations.
Configure a two-model OpenClaw fallback with Kimmy as the primary and GPT-5.nano as the fallback, with aliases and seamless switches via Telegram or TUI, enabling proactive scheduled messages.
Learn how OpenClaw uses Heartbeat and Cronjobs to run agents in the background, schedule context-aware turns, or predefined tasks, and understand their mental model.
Configure the OpenClaw heartbeat to run at a set interval, route output to telegram via target and to fields, create heartbeat.md templates, then restart the gateway and verify via logs.
OpenCLA uses AGENTS.md, sol.md, and identity.md to define the agent's rules, personality, and identity, with memory and transcripts stored in workspace files.
OpenClaw uses templates like user.md, tools.md, heartbeat.md, and bootstrap.md to define agent identity, environment context, and heartbeat behavior, with OpenClaw injecting only heartbeat.md when enabled to reduce token costs.
Configure a personalized AI agent by setting Identity.md, User.md, and Sol.md to define tone and preferences, so it monitors AI and tech breakthroughs and sends updates to telegram.
Understand how Nemo CLO adds security layer to OpenCLO by running agents inside OpenShell sandbox. Explore the four components—NVIDIA OpenShell runtime, blueprint system, inference routing, and the Nemo CLO CLI.
Set up a DigitalOcean VPS with Ubuntu 24.04 TLS, install Docker, create a dedicated Nemo CLO non-root user with passwordless sudo and SSH keys, update, and verify Docker access.
Are you seeing all the hype around AI agents, but not sure how to actually build one yourself?
This OpenClaw and Nvidia’s NemoClaw Crash Course gives you the practical skills to build real AI agents from scratch.
Imagine running your own AI agent… on your own server… connected to real tools like Telegram… automating tasks for you in the background.
No more just prompting AI. You’ll be building systems that actually work for you.
With step-by-step guidance, you’ll go from zero to launching your own AI agent using OpenClaw… and expand into more advanced systems with NVIDIA’s NemoClaw.
By the end, you’ll have real, working AI systems... and the skills to build more.
What You’ll Learn in This Course:
Build Your First AI Agent: Set up and run your own OpenClaw agent from scratch on a real server.
Understand AI Agent Architecture: Learn how modern AI agents work and how they differ from tools like ChatGPT and Claude.
Deploy on a Linux VPS: Launch and manage your own cloud server using DigitalOcean.
Install and Configure OpenClaw: Go step-by-step through installation, setup, and system configuration.
Secure and Optimize Your System: Harden your setup and manage services using systemd like a real developer.
Work with APIs: Connect your AI agent to external services using API keys and integrations.
Use Multiple Interfaces: Run and control your agent via terminal, web dashboard, and VS Code Remote SSH.
Integrate Real-World Tools: Connect your agent to Telegram and interact with it in real-time.
Automate with Cron and Heartbeats: Build agents that run continuously and perform scheduled tasks.
Build Practical AI Workflows: Apply your skills in hands-on projects using OpenClaw.
Explore Nvidia’s NemoClaw: Learn how advanced AI agent systems expand what’s possible beyond basic setups.
Understand Self-Hosted AI: Gain control over your own AI systems instead of relying on third-party tools.
With OpenClaw and NemoClaw skills, you unlock a whole new level of AI capability.
But what if this feels too technical?
No worries. We guide you step-by-step through everything—from server setup to running your first agent. You don’t need to figure this out on your own.
What if I’m not an expert developer?
That’s totally fine. If you’re comfortable using a computer and willing to follow along, you’ll be able to build your own AI agent system.
What if I don’t have time?
This is a crash course designed to get you results fast. Short, focused lessons let you build real skills without wasting time.
Through this course, you will:
❖ Build and deploy your own AI agent using OpenClaw
❖ Run AI systems on your own server with full control
❖ Connect AI agents to real tools like Telegram
❖ Automate workflows using cron jobs and persistent agents
❖ Expand into advanced agent systems with Nvidia’s NemoClaw
This OpenClaw & NemoClaw course isn’t just about learning AI…
It’s about building real systems that actually do things.
…and by the end, you won’t just be using AI tools, you’ll be creating your own.
Why Invest in OpenClaw and Nvidia’s NemoClaw Crash Course?
● Go Beyond Prompting: Move from using AI tools to building autonomous AI agents
● Real-World Skills: Learn practical deployment, automation, and system setup
● Self-Hosted Control: Run your own AI systems without relying on third-party platforms
● Future-Proof Your Skills: AI agents are one of the fastest-growing areas in tech
● Hands-On Learning: Build real working systems—not just theory
With these skills, you open doors to new opportunities:
AI Engineer
Build and deploy intelligent systems and AI-driven workflows
Automation Specialist
Create systems that automate tasks, saving time and increasing efficiency
DevOps / AI Ops Engineer
Manage and deploy AI systems in real-world environments
Technical Founder / Builder
Launch your own AI-powered tools, services, or products
Meet Your OpenClaw & NemoClaw Instructors: Phil Ebiner & Andrei Dumitrescu
Phil Ebiner is a top-rated instructor with millions of students worldwide, known for making complex topics simple and practical.
Andrei Dumitrescu is a software engineer and educator with 15+ years of experience, specializing in Python, systems, and real-world development.
Together, they combine clear teaching with hands-on technical depth to help you actually build things—not just learn about them.
Try it Risk-Free
You’re fully protected by Udemy’s 30-day money-back guarantee.
Jump in, start building your first AI agent, and see if this is the skill you’ve been looking for.
No risk. Just real skills.
Who Should Enroll:
● Developers who want to build AI agents and automation systems
● Tech enthusiasts curious about how AI agents actually work
● Entrepreneurs looking to build AI-powered tools or products
● DevOps engineers interested in deploying AI systems
● Anyone ready to move beyond ChatGPT and start building real AI systems
Stop just using AI…
Start building it.
Enroll now and launch your first AI agent today.