Module 1 - Introduction to Data Science
Segment - 01 - Introduction to the Course
Segment - 02 - Data Analysis and Data Mining
Segment - 03 - Software Choices for Data Analysis
Segment - 04 - What is R?
Segment - 05 - Steps in the Analytics Exercise
Segment - 06 - Analytics Capabilities Framework
Segment - 07 - The Job of the Data Scientist
Module 2 - R Studio and Getting Started with R
Segment - 08 - Getting Started with R and Installation
Segment - 09 - Things to Know About R and Its Packages
Segment - 10 - Getting a Feel for R Some Examples
Segment - 11 - Lists and Factors
Segment - 13 - DataFrame Basics
Segment - 12 - Matrices
Segment - 14 - Getting Data Into R and Managing Data
Segment - 15 - Loops and Flow Controls
Segment - 16 - Functions in R
Segment - 17 - What to do When You Need Help
Segment - 18 - R and R Studio in Action
Segment - 19 - Vectorized Operations
Segment - 20 - Matrices in R
Module 3 - Data Manipulation Techniques - Part 1
Segment - 21 - What is Data
Segment - 22 - Types of Data Sets
Segment - 23 - Preparing Data and Data Integration
Segment - 24 - Handling Missing Data and Values
Segment - 25 - Handling Outliers
Segment - 26 - Data Transformation
Segment - 27 - Handling Duplicate Data
Module 4 - Data Manipulation Techniques - Part 2
Segment - 28 - Getting to Know the Data
Segment - 29 - Relationships Between Variables
Segment - 30 - Data Aggregation
Segment - 31 - Sub-setting
Segment - 32 - Sorting and Ordering
Segment - 33 - Merging Matrices and DataFrames
Module 5 - Advanced Data Manipulation
Segment - 34 - dplyr
Segment - 35 - Other Functions in dplyr
Segment - 36 - Still More Functions in dplyr
Segment - 37 - Apply Function
Segment - 38 - What is Data Visualization
Module 6 - Visualization
Segment - 39 - Graphics in R
Segment - 40 - Graphing Basics in R
Segment - 41 - ggplot
Segment - 42 - ggplot2
