Section 1 : Course Introduction
Section 2 : Course Best Practices
Section 3 : Windows Installation Set-Up
Section 4 : Mac OS Installation Set-Up
Section 5 : Linux Installation
Section 6 : Development Environment Overview
Section 7 : Introduction to R Basics
Section 8 : R Matrices
Section 9 : R Data Frames
Section 10 : R Lists
Section 11 : Data Input and Output with R
Section 12 : R Programming Basics
Section 13 : Advanced R Programming
Section 14 : Data Manipulation with R
Section 15 : Data Visualization with R
Section 16 : Data Visualization Project
Section 17 : Interactive Visualizations with Plotly
Section 18 : Capstone Data Project
Section 19 : Introduction to Machine Learning with R
Section 20 : Machine Learning with R - Linear Regression
Section 21 : Machine Learning Project - Linear Regression
Section 22 : Machine Learning with R - Logistic Regression
Section 23 : Machine Learning Project - Logistic Regression
Section 24 : Machine Learning with R - K Nearest Neighbors
Section 25 : Machine Learning Project - K Nearest Neighbors
Section 26 : Machine Learning with R - Decision Trees and Random Forests
Section 27 : Machine Learning Project - Decision Trees and Random Forests
Section 28 : Machine Learning with R - Support Vector Machines
Section 29 : Machine Learning Project - Support Vector Machines
Section 30 : Machine Learning with R - K-means Clustering
Section 31 : Machine Learning Project - K-means Clustering
Section 32 : Machine Learning with R - Natural Language Processing
Section 33 : Machine Learning with R - Neural Nets
Section 34 : Machine Learning Project - Neural Nets