Course details

R for Data Science: Classification & Clustering

R for Data Science: Classification & Clustering


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore the advantages of the programming language R in this 8-video Skillsoft Aspire course. An essential skill for statistical computing and graphics, R is the tool of choice for data science professionals in every industry and field. It both creates reproducible high-quality analyses, and offers unparalleled graphic and charting capabilities. Learners will examine how to apply classification and clustering methods to data science problems by using R. Key concepts covered in this course include performing the preparatory steps needed to create a classification and decision tree; using the rpart library and ctree library to build a decision tree; and how to perform the preparatory steps needed to carry out clustering. Next, explore use of the k-means clustering method; using hierarchical clustering with the hclust and cutree methods; and applying a decision tree method to a classification problem. Finally, learn to train a decision tree classifier by using the data and a relationship inside of those data.



Expected Duration (hours)
0.6

Lesson Objectives

R for Data Science: Classification & Clustering

  • Course Overview
  • perform the preparatory steps needed to create a classification and decision tree
  • use the rpart library to build a decision tree
  • use the ctree library to build a decision tree
  • perform the preparatory steps needed to carry out clustering
  • use the k-means clustering method
  • use hierarchical clustering with the hclust and cutree methods
  • apply a decision tree method to a classification problem
  • Course Number:
    it_dsrfdsdj_05_enus

    Expertise Level
    Intermediate