Skip to content

Latest commit

 

History

History
45 lines (33 loc) · 2.19 KB

resources.md

File metadata and controls

45 lines (33 loc) · 2.19 KB
Raw

Learn to code!

  1. A complete course https://www.learnpython.org
  2. Ditto https://www.w3schools.com/python/
  3. Advanced course https://automatetheboringstuff.com

How to install Python?

  1. Just Python https://www.python.org/downloads/
  2. The Jupyter Notebook (the thing you are working with today) https://jupyter.org/install
  3. Anaconda (a collection of useful packages and other software for data scientists) https://www.anaconda.com/distribution/

Text editors

Note: If you don't use notebooks, you'll need a text editor to write your Python code. Don't use Microsoft Word! You want something that automatically highlights code (and makes it easier to distinguish variables, functions and the like), and provides autocompletion (saves A LOT of time).

Below are a few free and popular choices:

  1. Atom editor https://atom.io/
  2. Visual Studio Code https://code.visualstudio.com/
  3. Sublime https://www.sublimetext.com/

All these editors support multiple programming languages. I write my Python, Matlab, Javascript code and documentation in Markdown or Latex in Atom. Saves so much time!

All-in-one solutions

You can also use an all-in-one solution that provides you with an editor, code interpreter (the thing that allows the computer to read and execute Python code) and file managers (a bit like the Matlab software or R-Studio, which you might have heard of).

For Python, you can use:

  1. Spyder (free) https://www.spyder-ide.org/
  2. Pycharm (free basic and commercial pro version) https://www.jetbrains.com/pycharm/

Coding challenges

These challenges are a great way to test your understanding of computer science concepts and improve your logical thinking / problem solving skills.

Pro tip: Almost every company uses these challenges to assess candidates for software engineering and data science positions.

  1. Hackerrank https://www.hackerrank.com/
  2. Leetcode https://leetcode.com

Python for psychologists

You can use Python add-ons to run your own experiments, analyse behavioural, eye-tracking and neuroimaging data and to make beautiful visualisations of your results.

Below is a good starting point:

https://www.marsja.se/best-python-libraries-psychology/