Overview

Overview#

Now that you are equipped with powerful programming tools we can finally move into the world of applied modeling. In this module we’ll build on your new tools of data wrangling and programming to fit, analyze, and understand different applied modeling techniques. First, you will gain a basic understanding of discovering relationships across variables and using models for data exploration. Then you will learn about the machine learning process and how to start applying it with Python. This will give you the foundation to start building your own machine learning toolbox.

Learning objectives#

By the end of this module you should be able to:

  • Combine descriptive statistics and visualization to identify summaries, relationships, differences, and abnormalities in the data.

  • Explain the modeling process and apply it within your Python workflow.

  • Apply and explain the results of a few foundational machine learning algorithms using Scikit-learn.

Estimated time requirement#

The estimated time to go through the module lessons is about 3-4 hours.

Contents