R Programming for Data Science

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: What is R ?

Lecture 3: Why Learn R ?

Lecture 4: Features of R Language

Lecture 5: Importance of R in Data Science

Lecture 6: Advantages of using R

Lecture 7: Applications of R Programming

Lecture 8: Career Opportunities and Job Roles

Chapter 2: Getting Started with R

Lecture 1: Installing R Software

Lecture 2: Installing RStudio

Lecture 3: Look around RStudio Interface

Lecture 4: Help & Examples Facility for R Features and Functions

Lecture 5: Changing Look and Feel of RStudio (Optional)

Lecture 6: Some General Functions Good to Know

Lecture 7: Writing R Program using RGui

Lecture 8: Writing R Program using RStudio

Lecture 9: Using Comments in R Scripts

Chapter 3: R Basics

Lecture 1: Using R for Arithmetics

Lecture 2: Using Mathematical Functions

Lecture 3: Variables

Lecture 4: Keywords or Reserved Words

Lecture 5: Simple Program to Compute Interest

Lecture 6: Variable Assignments

Lecture 7: Displaying Output

Lecture 8: Reading Input

Chapter 4: Data Types

Lecture 1: Statically and Dynamically Typed Languages

Lecture 2: Atomic Data Types

Lecture 3: Numeric Type

Lecture 4: Integer Type

Lecture 5: Complex Type

Lecture 6: Logical Type

Lecture 7: Character Type

Lecture 8: Type Conversions

Lecture 9: Conversion to Numeric Type

Lecture 10: Conversion to Integer Type

Lecture 11: Conversion to Complex Type

Lecture 12: Conversion to Logical Type

Lecture 13: Conversion to Character Type

Chapter 5: Operators in R

Lecture 1: Operators – Introduction

Lecture 2: Relational Operators

Lecture 3: Logical Operators

Chapter 6: Vectors

Lecture 1: Creating Vectors

Lecture 2: Subsetting Vectors

Lecture 3: Matching Operator

Lecture 4: Vector Arithmetic

Lecture 5: Vector Methods & Operations

Lecture 6: Implicit & Explicit Coercion

Lecture 7: Logical Vectors

Lecture 8: Mathematical Functions

Lecture 9: Generating Random Numbers

Lecture 10: Sequences

Lecture 11: Replicate

Chapter 7: Matrices

Lecture 1: Creating Matrix

Lecture 2: Using diag() Function

Lecture 3: Naming Rows and Columns of Matrix

Lecture 4: Subsetting Matrix

Lecture 5: Martix rbind() and cbind()

Lecture 6: Matrix Operations

Lecture 7: Matrix Specific Function

Chapter 8: Lists

Lecture 1: Creating Lists

Lecture 2: Subsetting or Slicing List

Lecture 3: Naming List & Subset Operator

Lecture 4: Lists Concatenation

Chapter 9: Factors

Lecture 1: Factors

Chapter 10: Data Frames

Lecture 1: What are Data Frames?

Lecture 2: Creating Data Frames

Lecture 3: Subseting Data Frame

Lecture 4: Data Frame subset() function

Lecture 5: Data Frame rbind() and cbind() functions

Lecture 6: Data Frame edit() function

Lecture 7: Missing Data in Data Frames

Chapter 11: Control Structures

Lecture 1: Control Structures

Lecture 2: if, if-else and else-if statements

Lecture 3: ifelse() function

Lecture 4: for Loop

Lecture 5: while Loop

Lecture 6: repeat Loop

Lecture 7: break & next statement

Chapter 12: Functions

Lecture 1: Functions

Lecture 2: Default and Named Arguments

Lecture 3: Lazy Evaluation