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Udacity

Segmentation and Clustering

via Udacity

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Overview

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.

Syllabus

  • Segmentation and Clustering Fundamentals
    • Learn the difference between standardization and localization.,Learn about the concept of distance in clustering models.,Get introduced to how segmentation is used in business.
  • Data Preparation for Clustering Models
    • Learn how to select data for clustering models.,Learn what data types can be used in clustering models.,Scale and transform data for clustering models.
  • Variable Reduction
    • Learn the difference between factor analysis and principle components analysis.,Learn to use principal components analysis to reduce the number of variables in a model.
  • Clustering models design
    • Learn the difference between k-centroid and hierarchical clustering models.,Be able to select the number of clusters for a k-centroid model.,Validate your clusters in Alteryx.
  • Lesson 5 – Building a Clustering Model
    • Build a k-centroid clustering model to segment retail stores.,Learn how to visualize and validate your clusters.,Be able to interpret the results and communicate the “story” of the analysis.

Taught by

Rod Light

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