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Educational Resources

Table of Contents


This page lays out some useful educational resources for new participants to get started in Phase 1 of AI Campus. These resources are primarily aimed at participants that have little to no experience with Python programming, machine learning, or artificial intelligence in general.

Google Collaboratory Notebook

Google Colab is a framework allowing anyone to write and execute basic python code through the browser (rather than on your local computer). It’s easy to use since it comes pre-installed with python and many commonly used python packages for data science and machine learning. All you need to use it is a free google account.

Learn to Code in Python

One of the easiest ways to start learning Python is to open up a Google Colab notebook and begin trying out code within 'code cells'. You can use Google Colab to paste/try out code from other tutorials you find online to see the code working for yourself. There are also tutorials online that have their own build-in python interpreter so you can try out code in the tutorial's browser directly (e.g. DataCamp)

  • Basics of Python Programming (tutorial)
    • At the top of the page at this link, click on DataCamps 'Intro to Python tutorial' - the basics course is free, but more in-depth courses have a fee.
  • Learning Python - From Zero to Hero (Free)
  • Google's Python Class (Free)
  • Another very useful tool for learning to code Python is ChatGPT (free version)
    • At this link click 'Try ChatGPT', register and then use the text prompt to ask it things like - “write me python code to load a .csv dataset, and then print out a basic summary of that dataset”. You can copy the resulting code into your Google Colab or Jupyter Notebook to try it out.
    • ChatGPT works really well for basic coding requests, but for more complicated requests it can make mistakes or misunderstand what you want the code to do.

Installing Python, Anaconda and Jupyter Notebook

If you want to use Jupyter Notebook, or some other IDE on your computer, you'll need to install some basic things first. This is called setting up your computing 'environment'. To code and run Python code on your computer, you'll need to install Python3 at minimum. Generally, we recommend installing Anaconda3, which comes with Python3 as well as most standard data science and machine learning packages you'll want to use. Other packages you may want to use along the way can be installed later using 'pip' and/or 'conda' installation commands.

Basic Concepts of Machine Learning and/or Data Science

Coding a Machine Learning and/or Data Science Pipeline