Data Academy Subscription > Data with R > Introduction to Clustering Methods
Course Description
In this course, you will study the most basic type of unsupervised learning, clustering. You will learn what clustering is, its types, and when and how to create clusters with any type of dataset. You will perform k-mean and k-medoids algorithms, and determine the optimum number of clusters.
Requirements
  • This course assumes prior programming knowledge in R and a basic knowledge of mathematical concepts, including exponents, square roots, means, and medians.
Instructor:
Bert Gollnick
Bert Gollnick has a diploma in Aerospace Engineering and has pursued MSc in Economics. He is also a Data Scientist and has 10 years of experience in R. He is also an online trainer for Data Science and Machine Learning.