Course curriculum

  • 1

    Module 01: Course Introduction

    • Segment - 01 - Introduction
    • Segment - 02 - Install R and RStudio
    • Segment - 03 - Common Data Types
  • 2

    Module 02: Read in Data From Different Sources

    • Segment - 04 - Read in CSV and Excel Data
    • Segment - 05 - Read in Data from Online HTML Tables - Part 1
    • Segment - 06 - Read in Data from Online HTML Tables - Part 2
    • Segment - 07 - Read in Data from Databases
    • Segment - 08 - Read in Data from JSON
  • 3

    Module 03: Data Processing With dplyr

    • Segment - 09 - Introduction to Pipe Operators
    • Segment - 10 - Get acquainted with our data using "dplyr"
    • Segment - 11 - More selections with dplyr
    • Segment - 12 - Row Filtering
    • Segment - 13 - More Row Filtering
    • Segment - 14 - Select desired Rows and Columns
    • Segment - 15 - Add new variables/columns
    • Segment - 16 - Making sense of data by grouping different categories
    • Segment - 17 - Grouping Data - Part 2
    • Segment - 18 - Introduction to dplyr for Data Summarizing - Part 1
    • Segment - 19 - Introduction to dplyr for Data Summarizing - Part 2
  • 4

    Module 04: Data Processing the Tidy Way: The "tidyr" Package

    • Segment - 20 - Start with Tidyverse
    • Segment - 21 - Column Renaming
    • Segment - 22 - Tidy Data: Long and Wide
    • Segment - 23 - Joining Tables
    • Segment - 24 - Nesting
    • Segment - 25 - Brief Reminder: Hypothesis Testing
    • Segment - 26 - Implement t-test On Different Categories
  • 5

    Module 05: Dealing With Missing Values

    • Segment - 27 - Removing NAs- the ordinary way
    • Segment - 28 - Remove NAs- using "dplyr"
    • Segment - 29 - Data Imputation with dplyr
    • Segment - 30 - More Data Imputation
  • 6

    Module 06: Data Visualization and Explorations

    • Segment - 31 - What is Data Visualization?
    • Segment - 32 - Some Principles of Data Visualization
    • Segment - 33 - Data Visualization With dplyr and ggplot2
    • Segment - 34 - Mining and Visualizing Information About the Olympic Games
    • Segment - 35 - Of Winter and Summer Olympic Games
    • Segment - 36 - Of Men and Women
    • Segment - 37 - Theory of Ordinary Least Square (OLS) Regression
    • Segment - 38 - Implement OLS on Different Categories