Use machine learning to create segments
The Segmentation and Clustering course provides students with the foundational knowledge to build and apply clustering models to develop more sophisticated segmentation in business contexts. You will learn:
The key concepts of segmentation and clustering, such as standardization vs. localization, distance, and scaling
The concepts of variable reduction and how to use principal components analysis (PCA) to prepare data for clustering models
How to choose between hierarchical and k-centroid clustering models
How to build and apply k-centroid clustering models
Throughout this course you’ll also learn the techniques to apply your knowledge in a data analytics program called Alteryx.
This course is part of the Business Analyst Nanodegree Program.
Rich Learning Content
Taught by Industry Pros
Student Support Community
See the Technology Requirements for using Udacity.
Segmentation is used by companies across industries to better target the right products to the right customers. Most segmentation approaches are rather simple, such as segmenting customers by geography or age. However, with the rich amount of data business have now, much more sophisticated segmentation approaches are available.
In this course, you'll learn how to use an advanced analytical method called clustering to create useful segments for business contexts, whether its stores, customers, geographies, etc.
You'll learn this through improving your fluency in Alteryx, a data analytics tool that enables you prepare, blend, and analyze data quickly.
This course is ideal for anyone who is interested in pursuing a career in business analysis, but lacks programming experience.