Udacity: Segmentation and Clustering Review

Udacity's Segmentation and Clustering is a free self-paced introduction to common unsupervised learning methods for grouping data geared toward students interested in its Business Analyst Nanodegree Program. The 3-week course requires no programming knowledge and has no other prerequisites aside from downloading the Alteryx data analytics software if you want to follow along with the program demonstrations. The course does not have graded assignments, but there are a few informal quizzes and exercises you can complete as you go along.


Course content is split up into 5 lessons: a general introduction to segmentation and clustering, preparing data for clustering, feature reduction techniques, clustering models and applying and validating clusters. Each lesson consists of 8 to 16 content segments, which take the form of 1 to 4 minute lecture videos and short quizzes. Although the lectures are short, the production quality is consistently excellent and the professor gives clear and concise explanations, making the course approachable even if you don't have an analytics or tech background. The Alteryx demonstrations will probably be the hardest part for most students to follow, particularly if you haven't taken any of the related courses that use the software. You could skip Alteryx demonstrations if learning about the software doesn't interest you.


Segmentation and Clustering is an short, approachable introduction to data clustering concepts with great lecture and video production quality. Although the course page suggests it will take about 3 weeks to complete, none of the 5 lessons take more than an hour to get through unless you spend extra time reading linked resources or playing around in Alteryx.


I give Segmentation and Clustering 4.5 out of 5 stars: Great.



Note: If you have a programming background and/or have interest in a course that goes into more depth on this subject, consider Machine Learning: Clustering & Retrieval offered by the University of Washington on Coursera.