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Tools

Before you can learn machine learning, you need a place to write code, a way to run it, and a way to save it. That is what this module sets up. Five tutorials, about two and a half hours in total.

Do them in order. Each one assumes the one before it is done.

The order of the five tutorials Zero day, then Git and GitHub, then Jupyter notebooks, then VS Code, then Python warm up. 1 Zero day 20 min 2 Git and GitHub 45 min 3 Notebooks 25 min 4 VS Code 35 min 5 Python warm up 60 min

  • Zero day

    Get your accounts working: the intranet, Slack, GitHub, and the cloud machine you will code on.

    Start

  • Git and GitHub

    Save snapshots of your work, put them online, and get your first project onto a profile employers will read.

    Start

  • Jupyter notebooks

    Run code one piece at a time and see the result immediately. This is where most of your experiments will happen.

    Start

  • VS Code

    The editor you will build real applications in, with Linux running underneath it.

    Start

  • Python warm up

    Loops, functions, lists, and dictionaries on realistic nested data. The skills every later module assumes.

    Start

Finish one before starting the next

It is tempting to skim all five and set things up later. Do not. Every tutorial after this module assumes your environment already works, and fixing it in week four costs far more than fixing it now.

What you will have at the end

A working Linux environment, code running in two places (notebooks for experiments, VS Code for real programs), and a GitHub repository with your first commits in it.