Frequently Asked Questions
Everything You Need to Know About This Local LLM Course
Common questions about the workshop, what to expect, and how to prepare.
What will I learn in this local LLM course for developers? +
In this local LLM course you will learn to run open weight models using Docker Model Runner, connect them to OpenClaw, build a complete private AI assistant, deploy it to WhatsApp or Telegram, and set it up on a VPS for always-on availability.
Which LLMs does this local LLM course cover? +
This local LLM course covers how to pull and run open weight models including Llama, Mistral, Phi and others using Docker Model Runner. You will learn how to select the right model for your hardware and configure memory limits appropriately.
Why should developers take a local LLM course instead of using cloud APIs? +
Cloud LLM APIs cost money per token, send your data to third party servers, and create API dependency. This local LLM course teaches you to run models on your own machine — zero ongoing costs, complete data privacy, and full control over your AI stack.
Do I need a powerful GPU to take this local LLM course? +
No GPU is required. Docker Model Runner can run open weight models on CPU with a minimum of 16GB RAM. The instructor will guide you through selecting appropriate models for your specific hardware during the live session.
Is this local LLM course suitable for Python developers with no Docker experience? +
Yes. This local LLM course is designed for Python developers. Docker experience is helpful but not required — the instructor covers Docker Model Runner setup from scratch during the live 4-hour session.
Will this local LLM course cover production deployment? +
Yes. The final module covers deploying your local LLM setup and OpenClaw assistant to a VPS server for always-on availability — so your AI assistant runs 24 hours a day without needing your laptop to be switched on.
