In layman terms, this is about getting results from that is skewed because of the input data.

You’ll learn this in your machine learning modules (19, 20, and 21) that a data model is highly dependent on the input data which you fed it. Thus, data collection techniques, cleaning and pre-processing is of supreme importance since it largely affects how your model is going to perform.

Algorithmic Bias Materials

Bootstrap Crash Course

I have created a public repo to demonstrate Bootstrap here:

The focal point is the layout of a page where you can render your data visualizations in. The rest is up to your experimentation, creativity and imagination.

We will not dive into front-end development or UX design because it is purely out of scope.