01. Project Introduction

Project Introduction

Welcome to the project for this part of the Nanodegree program. Now that you’ve learned about unsupervised learning techniques that allow you to summarize the dimensions of your data and cluster unlabeled data into groups with similar properties, it’s time to apply your knowledge to some real-life data.

In this project, our Bertelsmann partners AZ Direct and Arvato Financial Solutions have provided two datasets one with demographic information about the people of Germany, and one with that same information for customers of a mail-order sales company. You’ll look at relationships between demographics features, organize the population into clusters, and see how prevalent customers are in each of the segments obtained.

Before you begin, Timo will provide some background about the dataset, how it was prepared, and the tasks performed by a data scientist using this data.

We hope you’re excited to test your skills on some real-life data. Don’t forget that you’ll need to make use of more than what was covered in the preceding course. You’ll need to use wrangling techniques to organize the data into a form you can work with, and you’ll need to interpret the output of your operations.

The remainder of this lesson will provide you instructions for completing the project, and a rubric detailing how the project will be evaluated. Rise up to the challenge, and let’s see what patterns you can find in the data!