Computing Setup

A short, hands-on guide to getting your machine ready for scientific computing work. Inspect your hardware and operating system, install git, and learn enough to clone and pull from public repositories, which are the essentials to learn before getting started on any computing course or project.

Sections

#	Topic	Description
01	Know your machine	Identify your OS, CPU, RAM, storage, and GPU. Learn the commands to query each on macOS, Linux, and Windows, and understand how the WSL virtual machine differs from the physical hardware.
02	Git basics	Install git, configure your identity, clone a public repository, and pull updates. Pull-focused — authentication and pushing come later.
03	Editors	Install a modern code editor (VS Code recommended), add the essential extensions, and pick an AI coding extension. Configure a few settings that pay back the small investment quickly.

This guide is designed for students starting a computing course, but should be useful for anyone setting up a new machine or getting acquainted with one they already own.

Prerequisites

• A terminal: Terminal or iTerm on macOS, any terminal emulator on Linux, or PowerShell on Windows
• No prior command line or git experience required

Windows users: no extra setup to start. You can work through most of module 01 using PowerShell alone. You will want the Windows Subsystem for Linux (WSL) before tackling module 02 (git) and the optional WSL section at the end of module 01. See WSL.md when you get there.

Getting started

You can read each module right here on the web — no setup is needed to begin. Once you have completed module 02 (git), you can optionally clone the repository for offline access:

git clone https://lem.che.udel.edu/git/furst/computing-setup.git
cd computing-setup

Each section has its own README.md with a walkthrough and exercises.

Next steps

Once you are comfortable with your machine, can pull updates with git, and have a working editor, two companion guides build on this one:

• cli-walkthrough. A hands-on tour of the Unix command line, covering navigation, file manipulation, searching, processes, scripting, and remote access.
• coding-with-ai. Working effectively with AI coding assistants. The practice counterpart to module 03's setup: when to copy-paste, when to use the editor, when to use an agent, and how to verify and cite what comes out.

Either order works. Many readers will benefit from doing the cli-walkthrough first, since the command line shows up everywhere afterward.

License

MIT

Author

Eric M. Furst, University of Delaware