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- Level Beginner
- Duration 3 hours
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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.Auto Summary
Discover the essentials of customer segmentation in Python with Coursera's beginner-friendly course, designed for Data Science & AI enthusiasts. Over 2 hours, master Principal Component Analysis, Kernel PCA, and K-Means Clustering to analyze customer purchase data. Ideal for North American learners, this free course equips you with the skills to identify customer similarities and differences using unsupervised machine learning techniques. Join now and enhance your data analysis capabilities!