You will find the following hands-on resources for each step:

  • Solved exercises: Notebooks that have a detailed explanation in a video. They are useful examples that illustrate each step of the standard process of building machine learning models;
  • Tutorial: Supporting documents with detailed explanations of the concepts given in the videos. In addition, the tutorials also have more examples that allow you to see how the concepts apply in practice. The tutorials can be read from start to finish or used as a reference source whenever you need to know more about something;
  • Cookbooks: Collections of small programs that solve typical situations. In general, cookbooks are useful when you want to solve a routine problem and need code examples to make your work easier.

We encourage you to post questions and remarks about all these notebooks in the discussion Forum.

In this first edition, we decide not to include the partially solved exercises and open exercises that could be resources of self-regulated learning because it would make the course too heavy in terms of workload.