openclaw docker workshop · Live · April 26

The OpenClaw Docker Workshop That Gets You Building in 4 Hours

Stop searching for scattered tutorials. This live OpenClaw Docker workshop takes you from zero to a fully deployed private AI assistant in one 4-hour session — with a live instructor guiding every step.

Sunday, April 26 9am to 1pm EDT

4 Hours Hands-on coding

Live Online Interactive

Workshop Details

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Date and Time

Sunday, April 26, 2026

9:00am to 1:00pm EDT

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Duration

4 Hours · Hands-on

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Format

Live Online · Interactive

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Includes

Certificate of Completion

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Privacy

100% Local · No Cloud Required

By Packt Publishing · Refunds up to 10 days before

About This OpenClaw Docker Workshop

Why This OpenClaw Docker Workshop is Different From Everything Else

Most tutorials show you isolated steps. This openclaw docker workshop gives you a complete guided build with a live expert answering your specific questions throughout.

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What is OpenClaw?

OpenClaw is the open-source personal AI assistant that went viral in early 2026 with 200K+ GitHub stars. It runs on your own devices and connects to WhatsApp, Telegram, Slack and more. No subscription. No data leaving your machine.

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What is Docker Model Runner?

Docker Model Runner is Docker's native feature for running large language models locally on your machine. It gives you an OpenAI-compatible API that OpenClaw uses as its AI brain — complete data privacy, no cloud costs.

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Why combine OpenClaw and Docker?

OpenClaw gives you the assistant interface and messaging integrations. Docker Model Runner gives you the AI brain running privately on your machine. Together they create a production grade private AI assistant you fully own.

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Why attend this as a live workshop?

Setting this up from scattered documentation takes days of debugging. This openclaw docker workshop gives you a complete guided build in 4 hours with a live instructor answering your questions. Packt has delivered 108 workshops worldwide.

Workshop Curriculum

What You Will Build in This OpenClaw Docker Workshop

Six modules. Four hours. One working private AI assistant by the time you finish.

How OpenClaw Works

Understand the Gateway, channels, and skills architecture. Set up and configure OpenClaw locally from scratch.

Docker Model Runner Setup

Run and manage local LLMs using Docker Model Runner. Pull models, configure memory, understand the OpenAI-compatible API.

Security and Privacy

Configure DM pairing, allowlists, sandbox mode, and proper access controls for your local AI deployment.

Connect to WhatsApp or Telegram

Deploy your AI assistant to real messaging platforms without sending data to any third party cloud service.

Scalable Architecture

Design an extensible assistant architecture. Add skills, configure personality, set up proactive automation.

Production Deployment

Deploy your OpenClaw and Docker setup to a VPS for always-on availability running 24 hours a day.

What You Walk Away With

By the End of This OpenClaw Docker Workshop You Will Have

Concrete working deliverables — not just theory.

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A fully functional local AI assistant running on your machine

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Docker Model Runner configured with your chosen LLM model

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OpenClaw connected to WhatsApp or Telegram

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Security and privacy configuration you can trust

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A reusable architecture for future AI assistant projects

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Certificate of completion from Packt Publishing

Your Instructor

Learn from someone who has actually shipped this

This OpenClaw Docker Workshop is taught by a practitioner, not a YouTuber.

Rami Krispin

Workshop Instructor · April 26, 2026

Rami is a Senior Manager of Data Science and Engineering, Docker Captain, and LinkedIn Learning Instructor with deep expertise in building and deploying production AI systems. In this OpenClaw Docker Workshop he guides you step by step from a blank terminal to a fully deployed private AI assistant — answering your questions live throughout the 4-hour session.

Prerequisites

Who is This OpenClaw Docker Workshop For?

You do not need to be an expert. You do need the basics.

→ Basic familiarity with Python and APIs
→ A laptop with Docker installed (or willing to install before the session)
→ Minimum 16GB RAM recommended for smooth local AI inference
→ Optional: prior experience with LLMs or agent frameworks — helpful but not required

Frequently Asked Questions

Everything You Need to Know About This OpenClaw Docker Workshop

Common questions about the workshop, what to expect, and how to prepare.

What will I build in this OpenClaw Docker workshop? +

By the end of this OpenClaw Docker workshop you will have a fully working private AI assistant running locally on your machine, connected to WhatsApp or Telegram, powered by Docker Model Runner — with no cloud dependency and no ongoing subscription costs.

Is this OpenClaw Docker workshop suitable for beginners? +

This OpenClaw Docker workshop is designed for developers with basic Python and API familiarity. You do not need prior Docker experience. You do need Docker installed and a minimum of 16GB RAM for smooth local inference.

How is this live workshop different from watching a YouTube tutorial? +

YouTube tutorials show isolated steps. This live OpenClaw Docker workshop gives you a complete guided build with a real instructor answering your specific questions in real time. You also receive a Packt Publishing certificate of completion.

Will the OpenClaw Docker workshop be recorded? +

Yes. All registered participants receive a recording of the session so you can rewatch any part of the OpenClaw Docker workshop at your own pace after April 26.

What models will we run in this OpenClaw Docker workshop? +

The workshop covers how to pull and run open weight LLMs using Docker Model Runner. The instructor will guide you through selecting and configuring models appropriate for your hardware during the live session.

Do I need to install anything before the OpenClaw Docker workshop? +

Yes. You should have Docker installed on your laptop before attending. The instructor will walk you through the rest of the setup live during the OpenClaw Docker workshop session.