Let's get your computer set up for data science with Jupyter notebooks in Python, R, and Julia without installing any of that, and without using the command line.

1. Install Docker 🐳

Docker is a tool for downloading lightweight virtual machines called "containers" and running them in the background. We will use it to import all the data science tools in a container, to avoid installing them on your machine.

Install the Docker Desktop app using the instructions on its website. ➡️

Empowering App Development for Developers | Docker

2. Install Visual Studio Code 👩🏽‍💻

VS Code is an extremely popular coding editor and it integrates well with Docker.

Install VS Code using the instructions on its website. ➡️

Visual Studio Code - Code Editing. Redefined

3. Connect those two apps ⛓️

• Open VS Code.
• Open its Extensions marketplace with the icon shown in the image. ➡️
• Search for the "Remote - Containers" extension. It will empower VS Code talk to Docker.
• Click the blue button to Install it.

4. Open a project 📂

The first time you open a project takes a few steps:

• In VS Code, click the tiny green Remote - Containers button, as shown here. ➡️
• From the menu, choose Open Folder in Container...
• Choose the folder in which your data science project sits.
• From the menu, choose the Jupyter Data Science Notebooks container. (You may need to click the "Show all definitions..." to reveal it.)

Every later time you open that project will be shorter:

VS Code stored the choices you made above in a .devcontainer folder inside your project.

Next time you open the same folder, it asks if you want to use the same container. Say yes.