Centroid-based clustering organizes the data into non-hierarchical clusters, in contrast to hierarchical clustering defined below.
Centroid-based algorithms are efficient but sensitive to initial conditions and outliers. This course focuses on k-means because it is an efficient, effective, and simple clustering algorithm.
Example of centroid-based clustering.
K-means and K-medoids are the two most famous ones of this kind of clustering algorithms.