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Introduction to Course
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Course Curriculum
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What is Data Science?
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Windows Installation Procedure
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Mac OS Installation Procedure
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Development Environment Overview
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Course Notes
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Guide to RStudio
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Introduction to R Basics
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Arithmetic in R
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Variables
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R Basic Data Types
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Vector Basics
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Vector Operations
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Vector Indexing and Slicing
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Getting Help with R and RStudio
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Comparison Operators
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R Basics Training Exercise
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R Basics Training Exercise - Solutions Walkthrough
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Introduction to R Matrices
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Creating a Matrix
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Matrix Arithmetic
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Matrix Operations
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Matrix Selection and Indexing
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Factor and Categorical Matrices
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Matrix Training Exercise
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Matrix Training Exercises - Solutions Walkthrough
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Introduction to R Data Frames
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Data Frame Basics
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Data Frame Indexing and Selection
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Overview of Data Frame Operations - Part 1
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Overview of Data Frame Operations - Part 2
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Data Frame Training Exercise
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Data Frame Training Exercises - Solutions Walkthrough
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List Basics
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Introduction to Data Input and Output with R
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CSV Files with R
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Excel Files with R
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SQL with R
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Web Scraping with R
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Introduction to Programming Basics
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Logical Operators
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if, else, and else if Statements
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Conditional Statements Training Exercise
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Conditional Statements Training Exercise - Solutions Walkthrough
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While Loops
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For Loops
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Functions
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Functions Training Exercise
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Functions Training Exercise - Solutions
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Built-in R Features
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Apply
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Math Functions with R
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Regular Expressions
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Dates and Timestamps
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Data Manipulation Overview
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Guide to Using Dplyr
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Guide to Using Dplyr - Part 2
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Pipe Operator
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Dplyr Training Exercise
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Dplyr Training Exercise - Solutions Walkthrough
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Guide to Using Tidyr
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Overview of ggplot2
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Histograms
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Scatterplots
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Barplots
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Boxplots
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2 Variable Plotting
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Coordinates and Faceting
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Themes
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ggplot2 Exercises
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ggplot2 Exercise Solutions
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Data Visualization Project
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Data Visualization Project - Solutions Walkthrough - Part 1
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Data Visualization Project Solutions Walkthrough - Part 2
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Overview of Plotly and Interactive Visualizations
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Introduction to Capstone Project
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Capstone Project Solutions Walkthrough
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Introduction to Machine Learning
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Introduction to Linear Regression
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Linear Regression with R - Part 1
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Linear Regression with R - Part 2
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Linear Regression with R - Part 3
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Introduction to Linear Regression Project
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ML - Linear Regression Project - Solutions Part 1
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ML - Linear Regression Project - Solutions Part 2
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Introduction to Logistic Regression
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Logistic Regression with R - Part 1
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Logistic Regression with R - Part 2
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Introduction to Logistic Regression Project
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Logistic Regression Project Solutions - Part 1
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Logistic Regression Project Solutions - Part 2
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Logistic Regression Project - Solutions Part 3
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Introduction to K Nearest Neighbors
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K Nearest Neighbors with R
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Introduction K Nearest Neighbors Project
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K Nearest Neighbors Project Solutions
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Introduction to Tree Methods
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Decision Trees and Random Forests with R
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Introduction to Decision Trees and Random Forests Project
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Tree Methods Project Solutions - Part 1
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Tree Methods Project Solutions - Part 2
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Introduction to Support Vector Machines
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Support Vector Machines with R
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Introduction to SVM Project
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Support Vector Machines Project - Solutions Part 1
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Support Vector Machines Project - Solutions Part 2
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Introduction to K-Means Clustering
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K Means Clustering with R
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Introduction to K Means Clustering Project
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K Means Clustering Project - Solutions Walkthrough
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Introduction to Natural Language Processing
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Natural Language Processing with R - Part 1
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Natural Language Processing with R - Part 2
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Introduction to Neural Nets
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Neural Nets with R
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Introduction to Neural Nets Project
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Neural Nets Project - Solutions