Data Science with R Programming
About Course
We introduce R Programming for both beginners and professionals. In this course, you will get the basic and advanced concepts of data analysis and visualization using R Programming.
In this course, you will learn, how you can program in R and how you can use R for effective data analysis. This course covers the installation and configuration of the required software in order to analyze complex and realtime data.
During this course, you will get an opportunity to understand the practical issues in statistical computing that covers programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.
You will learn all the topics of R such as introduction, features, installation, Rstudio ide, variables, data types, operators, if statement, vector, data handling, graphics, statistical modeling, etc.
Course Curriculum
 R Programming Language
 R Installation
 RStudio User Interface
 Introduction to R Workspace
 Modify Global Options
 Managing Library of Packages
 Vector, Matrix, List, Arrays, DataFrames
 Assignment, Conditional, and Loop Expressions
 Using Logical, Math, and Statistical Functions
 Strings, Characters, Date Time Vectors
 Reading and Writing Data
 Visualizing the Data
 Project using Linear Regression
 Project Using Logistic Regression
 Project using Decision Tree
What I will learn?
 Course in the Hindi Language
 Earn a sharable certificate upon completion
 100% online course
 Complete the course according to your schedule
 Get tangible career benefits after completion of the course
 Approximately 55 hours of course content
 No hard prerequisites
Course Curriculum
Introduction to R Programming

R Programming Language
03:23 
Introduction to R
05:13 
R as Programming Language
04:48 
The need for R
06:00 
R Installation
03:26 
RStudio
01:49 
RStudio UI
02:06 
The Console
02:44 
The Editor
04:19 
The Environment Pane
02:32 
The History Pane
02:06 
The File Pane
01:19 
The plots pane
00:49 
The Package Pane
01:18 
The Help Pane
00:00 
The Viewer Pane
01:03
R Workspace Introduction
Introduction to R Workspace, R Working Directory, Create R Project in R Studio, Absolute and Relative Path, Managing the Project File

Introduction to R Workspace
01:30 
R Working Directory
05:33 
Create R Project in R Studio
03:31 
Absolute and Relative Path
06:33 
Managing the Project File
02:31
Inspecting an Environment
Topics Covered : Inspecting environment & symbols, View the structure of object, Removing Symbols

Inspecting environment & symbols
10:04 
View the structure of object
09:13 
Removing Symbols
02:01
Modifying Global Options
Topics Covered : Modify Global Options, Modifying the number of digits, Modifying the warning level

Modify Global Options
03:04 
Modifying the number of digits
07:40 
Modifying the warning level
07:53
Managing the library of packages
Topics Covered : Manage Package, Getting to know a package, Installing package from CRAN, Update package from CRAN, Install package from online repositories

Manage Package
03:32 
Getting to know a package
02:40 
Installing package from CRAN
05:51 
Update package from CRAN
03:10 
Install package from online repositories
01:39
Package Functions
Topics Covered : Package Function, Masking and name conflicts

Package Function
10:37 
Masking and name conflicts
05:19
R Basic Objects – Vector
Topics Covered  Basic Objects, Vector, Numeric Vector, Logic Vector, Character Vector, Sub setting Vectors, Named Vector, Extracting Elements, Class of the Vector, Converting Vectors, Arithmetic Operator

Basic Objects
03:24 
Vector
01:25 
Numeric Vector
12:04 
Logic Vector
11:04 
Character Vector
05:58 
Sub setting Vectors
17:02 
Named Vector
06:02 
Quiz – 1
00:00 
Extracting Elements
14:28 
Class of the Vector
02:28 
Converting Vectors
01:53 
Arithmetic Operator
08:08
R Basic Objects – Matrix
Topics Covered  Matrix, Naming Rows and Columns, Subset a Matrix, Matrix Operator

Matrix
15:21 
Naming Rows and Columns
03:20 
Subset a Matrix
10:51 
Matrix Operator
04:00
R Basic Objects – Array
Topics Covered  What is Array, Subset of Array, Homogeneous vs Heterogeneous Array

Array
04:25 
Subset of Array
04:02 
Homogeneous vs Heterogeneous Array
02:08
R Basic Objects – List
Topics  List, Extracting Element, Subset a List, Named List, Setting Values, Other List Operations

List
02:55 
Extracting Element
02:19 
Subset a List
02:25 
Named List
01:40 
Setting Values
03:34 
Other List Operations
02:44
R Basic Objects – Data Frame
Topics  Create Data Frame, Naming Row and Column, Subsetting Data Frame, Setting Values, Factors, Useful Functions for Data Frame, Loading and Writing Data to Disk

Create Data Frame
07:10 
Naming Row and Column
04:21 
Subsetting Data Frame
09:53 
Setting Values
07:13 
Factors
10:34 
Useful Functions for Data Frame
05:27 
Loading and Writing Data to Disk
03:44
R Basic Objects – Functions
Topics  Create and Call a Function, Dynamic Typing, Generalizing a Function, Default Value

Create and Call a Function
06:13 
Dynamic Typing
03:58 
Generalizing a Function
07:07 
Default Value
02:21
R Basic Expressions – Assignment Expressions
Topics  Basic Expressions, Assignment, Backtick

Basic Expressions
01:17 
Assignment
14:37 
Backtick
07:52
R Basic Expressions – Conditional Expressions
Topic  Conditional Expressions, Use if as a statement, Use if as an expression, Use if with vector, Vectorised if:ifelse, Switch function

Conditional Expressions
05:49 
Use if as a statement
18:42 
Use if as an expression
11:10 
Use if with vector
08:21 
Vectorised if:ifelse
08:38 
Switch function
04:54
R Basic Expressions – Loop Expressions
Topics  For Loops, For Loop  List & Data Frame, For Loop  Managing Flow, Nested For Loop, While Loop

For Loops
06:03 
For Loop – List & Data Frame
05:47 
For Loop – Managing Flow
06:09 
Nested For Loop
09:12 
While Loop
04:31
R Builtin Functions – Basic Objects
Topics  Overview of Basic Objects, Testing Object Type, Accessing Object Classes and Type, Getting Data Dimension, Reshaping Data Structure, Iterating Over One Dimension

Overview
03:09 
Testing Object Type
22:12 
Accessing Object Classes and Type
03:32 
Getting Data Dimension
05:18 
Reshaping Data Structure
03:21 
Iterating Over One Dimension
03:04
R Builtin Function – Logical Function
Topic  Logical Operators, Logical Functions, Which Elements are TRUE, NULL Values, Logical Coercion

Logical Operators
11:41 
Logical Functions
09:05 
Which Elements are TRUE
03:44 
NULL Values
05:60 
Logical Coercion
01:51
R BuiltIn Function – Math Function
Topics  Math Functions, Number Rounding Functions, Trigonometric Functions, Hyperbolic Functions, Extreme Functions

Math Functions
04:47 
Number Rounding Functions
03:22 
Trigonometric Functions
01:57 
Hyperbolic Functions
00:34 
Extreme Functions
06:03
R Builtin Function – Numeric Methods
Topics  Finding Roots, Derivatives, Integration

Finding Roots
06:23 
Derivatives
02:57 
Integration
01:36
R Builtin Function – Statistical Functions
Topics  Statistical Functions, Sampling from a Vector, Probability Distributions, Summary Statistics, Covariance and Correlation

Statistical Functions
01:00 
Sampling from a Vector
05:29 
Probability Distributions
06:29 
Summary Statistics
04:44 
Covariance and Correlation
05:15
R Strings – String and Character Vectors
Topics  Overview, Character Vectors, Printing Strings, Concatenating String, Transforming Text, Counting Characters, Trimming White Space, Substring, Splitting Text, Formatting Text

Overview
03:00 
Character Vectors
02:08 
Printing Strings
14:50 
Concatenating String
08:47 
Transforming Text
03:41 
Counting Characters
00:00 
Trimming White Space
02:13 
Substring
04:31 
Splitting Text
03:32 
Formatting Text
05:02
R Strings – Regular Expressions
Topics  Working with Regular Expressions, Finding a string pattern, Using Groups to Extract Data

Working with Regular Expressions
04:32 
Finding a string pattern
08:38 
Using Groups to Extract Data
04:55
R Date – Time Vectors
Topics  Date and Date/Time, Parsing Text as Date, Parsing Text as Time, Formating Text as Date/Time, Formatting date/time to string

Date and Date/Time
03:33 
Parsing Text as Date
03:10 
Parsing Text as Time
02:53 
Formating Text as Date/Time
07:20 
Formatting date/time to string
02:19
R Reading and Writing Data
Topics  Overview, Text format files, Importing data via RStudio, Importing data using builtin functions, Importing data using readr package, Reading Writing Excel Worksheets, Reading Writing Native Data File, Loading builtin datasets

Overview
03:02 
Text format files
01:57 
Importing data via RStudio
04:32 
Importing data using builtin functions
09:16 
Importing data using readr package
07:56 
Reading Writing Excel Worksheets
06:28 
Reading Writing Native Data File
04:46 
Loading builtin datasets
03:57
R Data Visualization – Overview
Topics  Introduction

Overview
03:29
R Data Visualization – Scatter Plot
Topics  Basic Scatter Plot, Scatter Plot  Two Vectors, Customize Chart Element, Customize Point Style, Scatter Plot  Logical Condition, Scatter Plot  Two Data Sets, Customize Point Colors

Basic Scatter Plot
02:02 
Scatter Plot – Two Vectors
04:16 
Customize Chart Element
04:33 
Customize Point Style
00:00 
Scatter Plot – Logical Condition
03:30 
Scatter Plot – Two Data Sets
07:31 
Customize Point Colors
05:20
R Data Visualization – Line Plot
Topics  Create Line Plot, Line Type and Width, Multiperiod Line Plot, Line Plot with Points, Multi series chart with legend

Create Line Plot
03:24 
Line Type and Width
12:48 
Multiperiod Line Plot
04:41 
Line Plot with Points
02:50 
Multi series chart with legend
04:34
R Data Visualization – Bar Chart
Topics  barplot(), Project NYCFlights  Part 1

barplot()
09:35 
Project NYCFlights – Part 1
05:32
R Data Vizualization – Pie Chart
pie()

pie()
03:22
R Data Vizualization – Histogram and Density Plot
Histogram, Project NYCFlights Part 2

Histogram
07:32 
Project NYCFlights – Part 2
05:46

LevelAll Levels

Duration55 hours 30 minutes

Last UpdatedJanuary 1, 2023
Hi, Welcome back!
Material Includes
 55 hours of digital content
 Ondemand videos
 Assignments
 Quizzes
 Projects
 Unlimited access for 1 year
 Certification on completion
Requirements
 Understand R Programming Concepts
 Learn how to use the R GUI called R studio
 Different data structures and data types in R
Skills You Will Gain
Target Audience
 School Students
 Engineering Students
 Management Students
 Working Professionals
 Faculty members and teachers