Introduction
Google Colab is a free cloud-based service that allows the execution of Python code using the Jupyter Notebook format. It is possible to use and install new python libraries. Furthermore it is possible to provide bash commands from the notebook and there are backdoor ways to even use R. The Python code uses only a CPU by default but Colab offers GPU (Graphics processing unit) as well as TPU (Tensor processing unit also for free. The notebook is following the Jupyter notebook standard and can be exported and used elsewhere (provided all requirements are met e.g. access to a GPU if that was coded within.)
Colab is heavily used for Machine Learning but can certainly be used as a platform to learn Python.
Note to University of Wisconsin users
UW personnel should use their G-Suite account to maintain and preserve Intellectual Property (IP) and other rules set for all Google Apps including Google Drive and more.
See G Suite (Formerly Google Apps) and UW-Madison G Suite – Usage Guidelines
Colab tutorials
The following 3 min video will provide a very good visual of what this is: Get started with Google Colaboratory also embedded below:
There are many free tutorials available online, including by Google Colab itself. Here is a non exclusive and non exhaustive links that I found useful:
- Directly on Google Colab itself – Welcome To Colaboratory
- Learn google Colab – Absolute beginners (by Tutorialpoint)
- Getting Started with Google Colab Notebooks – Uploading files, reading images, and more
- How to use Google Colab – Difficulty Level : Basic
- Google Colab 101 Tutorial with Python — Tips, Tricks, and FAQ An in-depth tutorial on how to use Google Colab with Python, along with Colab’s tips, tricks, and FAQ
- How to Connect Google Colab with Google Drive
- Google Colab Free GPU Tutorial
- Quick walkthrough (PDF)
- More advanced: Create your first machine learning model in 5 minutes with Google Colab
Python colab notebook example: