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Ultimate OpenClaw Local AI Assistant Mastery
Build Private On-Prem AI Agents, Local Tools, Skills, Automation & Knowledge Systems
5.021 reviews131 learners
- All Levels
- 7h 8m video
- 52 lectures
- English
- Captions
- Updated 2026
Taught by Medhat Gadallah
- 7h 8m of on-demand video
- 52 lectures across 10 sections
- One-off payment — no subscription
- Lifetime access on web and mobile
- Closed captions (English)
Curriculum
10 sections52 lectures7h 8m total
- Welcome to Ultimate OpenClaw Local AI Assistant Mastery4:35
- What This Course Is About ?5:56
- What This Course Is Not About ?5:06
- Why We Focus on Local and On-Prem AI ?5:33
- Who This Course Is For ?5:29
- What Is OpenClaw ?6:39
- OpenClaw as a Personal AI Assistant Gateway7:19
- OpenClaw vs Normal Chatbots6:30
- OpenClaw Architecture Big Picture8:21
- Gateway Explained6:45
- Channels Explained5:26
- Agents Explained5:12
- Skills Explained6:31
- Workspaces Explained5:50
- Sessions Explained5:33
- Local Tools Explained5:18
- Local Models Explained7:44
- Local Files and Permissions Explained6:57
- How a Message Flows Through OpenClaw9:22
- Local Lab Overview4:55
- Minimum Hardware Requirements7:42
- Windows Setup Options8:12
- Folder Structure for the Course7:57
- Installing VS Code7:37
- Installing Git7:21
- Installing Node.js7:20
- Installing Python5:32
- OpenClaw Installation Roadmap3:53
- Installing OpenClaw with npm7:15
- Running OpenClaw Onboarding11:59
- Installing the Gateway Daemon8:40
- Starting the Gateway Manually9:32
- Why Use Local Models?6:13
- What Is Ollama?4:36
- Installing Ollama6:44
- Running Your First Local Model6:29
- Pulling a Coding Model8:00
- Pulling a Reasoning Model7:02
- Connecting OpenClaw to Ollama25:25
About this course
Welcome to Ultimate OpenClaw Local AI Assistant Mastery — a complete hands-on course where you will learn how to build your own private, local, on-prem AI assistant system using OpenClaw. Most AI courses teach you how to chat with AI. This course teaches you how to build an AI assistant that can actually help you work with your files, documents, code, databases, tools, and daily workflows — all on your own machine. This course is designed with a strong local-first and on-prem mindset. That means we will focus on …
Before you start
- Basic computer skills are enough. You should be comfortable installing tools and using folders.
- A Windows, macOS, or Linux machine that can run Node.js and local development tools.
- Basic terminal knowledge is helpful, but every command will be explained step by step.
- No advanced AI experience is required. You will learn OpenClaw and local AI workflows from scratch.
- Basic programming knowledge is helpful for tool-building sections, but beginners can still follow along.
- For local AI models, 8 GB RAM minimum is recommended, and 16 GB or more is better.
- Internet is needed for initial installation, but the course focuses on local and on-prem workflows.
- A curious mindset and willingness to build practical AI automation projects locally.
Who it’s for
- Beginners who want to build a private local AI assistant using OpenClaw.
- Developers who want to automate coding, files, documents, APIs, and local workflows with AI.
- AI enthusiasts who prefer local and on-prem tools instead of depending on cloud AI platforms.
- IT professionals who want to explore private AI assistants for internal company workflows.
- Software testers who want to generate test cases, bug reports, dummy data, and QA documents locally.
- Content creators and Udemy instructors who want a local AI assistant for scripts, outlines, and course assets.
- Business users who want to automate local documents, reports, summaries, and admin tasks.
- Privacy-focused learners who want to keep files, documents, and knowledge bases on their own machine.
- Automation builders who want to connect OpenClaw with Shell, Python, Node.js, databases, and local tools.
- Anyone interested in building a complete local AI operating system using OpenClaw.
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