R Programming for Absolute Beginners

Course Curriculum

Chapter 1: Getting Started : Installation and Set Up

Lecture 1: Course Introduction

Lecture 2: Downloading Anaconda Distribution

Lecture 3: Complete Installation and Set up

Lecture 4: Installing R

Chapter 2: Handling Files in R

Lecture 1: Section Introduction | Learnings from this section

Lecture 2: Understanding Data

Lecture 3: Different Types of Data

Lecture 4: Create your own Data frame in R

Lecture 5: Import and Export a CSV File

Lecture 6: Import and Export an Excel File

Lecture 7: Import and Export JSON FIle

Chapter 3: R Basics : Variables and Data Types and Data Structure in R

Lecture 1: Section Introduction| | What you will learn

Lecture 2: What are variables and assigning data

Lecture 3: Understanding Data Types in R

Lecture 4: Data Types in R | Practical Exercise

Lecture 5: Understanding Data Structures in R

Lecture 6: What are Vectors, Understanding Vectors and Operations on Vectors

Lecture 7: What are Lists in R

Lecture 8: List | Create List and other functions

Lecture 9: What are Matrices in R

Lecture 10: Matrices Part 1: Create Matrices and operations in Matrix

Lecture 11: Matrices Part 2 | Matrix Calculations

Lecture 12: Understanding Data Frames in R

Lecture 13: DataFrames Part 1: Create a data frame in R , data exploration in R

Lecture 14: Data Frames Part 2: Adding Rows, Columns, Renaming Columns, Combining Data Frame

Lecture 15: Understanding Factors in R

Lecture 16: Factors | Create Factors and operations on Factors in R

Lecture 17: Understanding Arrays in R

Lecture 18: Arrays | Create Arrays and various Operations on Arrays

Lecture 19: Data Structures in R | Complete Wrap Up

Chapter 4: Data Manipulation in R | Introduction to dplyr , work with real data set

Lecture 1: Section Introduction | What you will learn

Lecture 2: Tidy Verse Brief Introduction

Lecture 3: Understanding dplyr

Lecture 4: Understanding The Pipe %>% Operator

Lecture 5: Loading Libraries, Loading Data Set and Data Exploration in R

Lecture 6: Understanding the Data Set : Data set Description

Lecture 7: Understanding arrange() function

Lecture 8: arrange() function Practice

Lecture 9: Exploring the Data in R | More Functions

Lecture 10: Understanding filter() function

Lecture 11: Filter() Function Practice

Lecture 12: Understanding select() function

Lecture 13: Select() Function Practice

Lecture 14: Dealing with NA's in the Data Frame

Lecture 15: Different Types of Missing Data

Lecture 16: Understanding summarize() function

Lecture 17: Summarize() function Practice

Lecture 18: Group_by() function Practice

Lecture 19: Understanding mutate() function

Lecture 20: Mutate() function Practice

Chapter 5: Understanding Different Charts in ggplot2

Lecture 1: Introduction to Data Visualization in R

Lecture 2: An introduction to ggplot2

Lecture 3: More on ggplot2 library

Lecture 4: Distribution Plots in R

Lecture 5: Composition Charts in R

Lecture 6: Correlation Plots in R

Lecture 7: Ranking Charts in R

Lecture 8: Grouped Plots in R

Lecture 9: Deviation Plots in R

Chapter 6: Data Visualization in R with ggplot2 | Working with different layers in ggplot2

Lecture 1: First Basic Plot With Basic layers | Adding Data, Aesthetics and Geometries

Lecture 2: Adding Labels to the Plot

Lecture 3: Adding Facets Layer

Lecture 4: Improving Facets | Dealing with NA's in the Plot

Lecture 5: Adding Coordinates Layer

Lecture 6: Adding Theme Layer

Lecture 7: Working with Scatter Plots

Lecture 8: Improved Scatter Plot with ggplot2 layers

Lecture 9: More Data For Practice

Chapter 7: Bonus Section

Lecture 1: Bonus