The Docker AI Engineering Workshop — Build Production AI Without the Cloud

This workshop focuses specifically on using Docker for AI workloads — running large language models with Docker Model Runner, building the OpenClaw assistant layer in Docker, and deploying the complete AI system using Docker infrastructure. It is Docker engineering applied to the specific challenge of building a production private AI assistant.

No. This Docker AI engineering workshop is designed for Python developers without prior Docker experience. The instructor covers the relevant Docker concepts as part of the live build — focusing on practical AI engineering rather than Docker theory.

After this workshop you will be able to use Docker Model Runner to run open weight LLMs, configure Docker networking for local AI applications, deploy Docker-based AI systems to a VPS, and manage model versions using Docker CLI commands. These are practical Docker AI engineering skills directly applicable to production work.

Yes. The OpenClaw and Docker Model Runner stack you build in this workshop uses standard Docker patterns and an OpenAI-compatible API. The architecture you learn applies to any project where you want to run AI locally using Docker — not just the OpenClaw personal assistant use case.

This workshop provides a Packt Publishing certificate of completion — not an official Docker certification. However, the Docker AI engineering skills you gain are directly applicable to real production Docker AI deployments.

The workshop primarily focuses on Docker Model Runner and the Docker CLI for model management. Docker Compose patterns for the OpenClaw setup are briefly covered. The instructor can answer specific Docker Compose questions during the live Q and A portion of the session.