Prepare customer data in Python, apply supervised regression and unsupervised k-means/PCA, evaluate clusters and translate segments into targeted marketing actions
Prepare customer data in Python, apply supervised regression and unsupervised k-means/PCA, evaluate clusters and translate segments into targeted marketing actions
Practice and assessment
Practice: A quiz on analytics fundamentals is listed
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Prepare and evaluate k-means, hierarchical and DBSCAN clusters, then complete an ecommerce customer-segmentation project, broader unsupervised ML supports the marketing application
11 sections • 52 lectures • 4h 53m total lengthCheck current priceEnglish
Prepare customer data, apply hierarchical/k-means/PCA segmentation, analyze purchase data by segment and model purchase incidence, marketing mix and price response
13 sections • 76 lectures • 5h 11m total lengthCheck current priceEnglish