YoVDO

Customer Segmentation using K-Means Clustering in R

Offered By: Coursera Project Network via Coursera

Tags

R Programming Courses Data Visualization Courses R Markdown Courses Customer Segmentation Courses ggplot2 Courses K-Means Clustering Courses

Course Description

Overview

Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages.
By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing.
Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

Syllabus

  • Project Overview
    • Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages. By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing. Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!

Taught by

Arimoro Olayinka Imisioluwa

Related Courses

Aprendizaje de máquinas
Universidad Nacional Autónoma de México via Coursera
Applied Artificial Intelligence: Computer Vision and Image Analysis
Cloudswyft via FutureLearn
Introduction to Customer Segmentation in Python
Coursera Project Network via Coursera
Foundations of Data Science: K-Means Clustering in Python
University of London International Programmes via Coursera
Data Science Projects and Applications
Packt via FutureLearn