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### Machine Learning Examples for Data Science in R

**Overview/Description**
**Target Audience**
**Prerequisites**
**Expected Duration**
**Lesson Objectives**
**Course Number**
**Expertise Level**

**Overview/Description**
R is a free software environment for statistical computing and graphics and has become an important tool in modern data science. In this course, you will learn the essential R machine learning methods that data scientists use in their everyday work.

**Target Audience**
Individuals with some statistics, programming, and machine learning experience who wish to learn machine learning methods in R used in data science in R

**Prerequisites**
None

**Expected Duration (hours)**
2.5

**Lesson Objectives****Machine Learning Examples for Data Science in R**

start the course
distinguish between supervised and unsupervised learning
perform classical multidimensional scaling using cmdscale in R
perform hierarchical cluster analysis in R
use the corclust function in the klaR package in R
perform k-means clustering on data in R
use the kselection package to select k for a k-means clustering in R
use the clusplot function to perform a cluster plot on a clara object in R
perform a fully C-Means clustering from the e1071 package in R
create a basic classification tree using rpart in R
create a basic regression tree using rpart in R
create a basic classification tree with the trees package in R
create a basic regression tree with the trees package in R
perform a K-Nearest Neighbor classification in R
use the randomforest package for classification in R
combine random forest ensembles into a single object in R
use random forests for unsupervised classification in R
use the clusplot function to perform a cluster plot on a pam cluster in R
build a naïve bayes classifier using the klaR package in R
use the lda function in R
use the qda function from the MASS package in R
perform a MDS using the mda package in R
use the SVM function from the e1071 library in R
perform a curve fit using the LOESS method in R
perform a PLS regression using the pls package in R
plot a smoothing spline from the splines packages in R
use the boosting function from the adabag package in R
use the bagging function from the adabag package in R
create a scatterplot matrix using the caret package in R
create an overlayed density plot using the caret package in R
create a 3D Scatterplot in R
provide a basic understanding of how to use common statistical methods for data analysis in R
**Course Number:**df_dsfd_a02_it_enus

**Expertise Level**
Intermediate