Introduction to Data Science: Data Analysis and Prediction Algorithms with R

Covers the basics of R and the tidyverse
Demonstrate how to use ggplot2 to generate graphs and describe important Data Visualization principles Introduces Data Wranglin topics such as web scrapping, using regular expressions, and joining and reshaping data tables using the tidyverse tools
Illustrates the importance of statistics in data analysis using case studies
Uses the caret package to build prediction algorithms including K-nearest Neighbors and Random Forests Includes tools used on a day-to-day basis in data science projects including RStudio, UNIX/Linux shell, Git and GitHub, and knitr and R Markdown