> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Virtualization

> Choosing between the course Docker containers and a native installation, and where each one applies.

Docker containers are the default for course work, and on Windows and Linux they are what you should use. The guide below covers installation for all three platforms plus the build and run commands.

<Card title="Docker Containers" icon="docker" href="/aiml-common/resources/environment/docker-containers" cta="View guide">
  Docker installation, course environment setup, ROS on Mac, and all build and run commands.
</Card>

On an Apple Silicon Mac the container cannot reach the GPU, because Metal is not exposed to the Linux virtual machine Docker runs. For the AI and computer vision courses you can install natively instead and use the GPU through Metal. For robotics the container is still required, since ROS 2 does not run natively on macOS.

<Card title="macOS Native" icon="apple" href="/aiml-common/resources/environment/macos-native" cta="View guide">
  Installing natively on Apple Silicon with uv, using the PyTorch mps device, and what you give up by leaving the container.
</Card>

Either way you will need Python and `uv` to manage dependencies.

<Card title="Python & uv" icon="python" href="/aiml-common/resources/environment/python-uv" cta="View guide">
  Installing Python, managing virtual environments, and installing packages with uv, the fast, modern replacement for pip and conda.
</Card>

***

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  [Edit this page on GitHub](https://github.com/aegean-ai/eaia/edit/main/src/aiml-common/resources/environment/virtualization.mdx) or [file an issue](https://github.com/aegean-ai/eaia/issues/new/choose).
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