This lesson gives an overview of the course.

This lesson introduces R and R Studio and shows the integrated development environment and the R Notebook.

This lesson digs into the Titanic dataset and uses visualizations to explore how different factors impact the survival rate of the passengers.

This lesson briefly introduces machine learning and how we see machine learning models as black boxes.

This lesson shows the use of a conditional inference tree to predict the survival of passengers.

This lesson shows the use of Naïve Bayes to predict the survival of passengers.

This lesson shows the use of k-Nearest-Neighbor to predict the survival of passengers.

This lesson compares the tree machine learning models, and provides some suggestions for further reading.