Related skills · check the marketing fit
Prepare and evaluate k-means, hierarchical and DBSCAN clusters, then complete an ecommerce customer-segmentation project, broader unsupervised ML supports the marketing application
Meta Brains , Skool of AI · Udemy
Prepare and evaluate k-means, hierarchical and DBSCAN clusters, then complete an ecommerce customer-segmentation project. Broader unsupervised ML supports the marketing application
Selected published requirements: “Basic understanding of Python programming is helpful but not required”. “No prior knowledge of machine learning or clustering is needed”. See the provider page for the full requirements and current tool terms
Recorded Udemy course advertised with a public course preview. Exact lesson count may be unknown. Purchase or organization-subscription terms and current availability require checking
Related tasks, tools and formats. Check the differences before choosing.
Tobias Mayer
Prepare customer data in Python, apply supervised regression and unsupervised k-means/PCA, evaluate clusters and translate segments into targeted marketing actions
Taman Belajar, Bina Nusantara University
Prepare customer data, implement k-means in Python, evaluate and interpret clusters and complete a customer-segmentation case study
O.P. Jindal Global University
Python marketing workflows cover k-means, hierarchical and DBSCAN segmentation, PCA, t-SNE and autoencoders, anomaly detection, association mining, semi-supervised methods, and recommender systems