Introduction to Customer Segmentation in Python

Offered By
Coursera Project Network
In this Guided Project, you will:

Dimensionality Reduction using standard PCA and variants

Create interactive plots

Clustering data using K-Means with evaluation metrics

Clock2 hours
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2 hour long project, you will learn how to approach a customer purchase dataset, and how to explore the intricacies of such a dataset. You will learn the basic underlying ideas behind Principal Component Analysis, Kernel Principal Component Analysis, and K-Means Clustering. You will learn how to leverage these concepts, paired with industry knowledge and auxiliary modeling concepts to segment the customers of a certain store, and find similarities and differences between different clusters using unsupervised machine learning techniques. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Dimensionality ReductionMarket SegmentationMachine Learningclustering

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction to the task and demo

  2. Exploratory Data Analysis

  3. Principal Component Analysis

  4. Kernel Principal Component Analysis

  5. K-Means Clustering

  6. Interactive Cluster Analysis

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.