In this module, you will earn the basics of R and RStudio, starting from the installation processes. You will get an overview of the RStudio environment, the R commands you can use to input data, and the packages and data available in R. You will also learn to create graphs, change colours, and save the graphs.

This module explains the concept of Support Vector Machines (SVM), starting with the concept of machine learning and the steps to build a machine learning model. You will learn the importance of data pre-processing and classification using the Maximum Margin Classifier, of which the SVM is an extension. You will also learn the concepts of hyperplanes and kernels, which are vital to understanding data processing and machine learning algorithms.

This module takes you back to the RStudio, where you will learn how to create an SVM model in R. You will begin by loading the data, then training and testing the data to build the classification model. This will be followed by tuning the hyperparameters to get better results. You will also learn to build a regression model using the same data set but different variables.