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 real-time 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 Built-in 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 Built-in 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 Built-In 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 Built-in Function – Numeric Methods
Topics - Finding Roots, Derivatives, Integration
-
Finding Roots
06:23 -
Derivatives
02:57 -
Integration
01:36
R Built-in 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 built-in functions, Importing data using readr package, Reading Writing Excel Worksheets, Reading Writing Native Data File, Loading built-in datasets
-
Overview
03:02 -
Text format files
01:57 -
Importing data via RStudio
04:32 -
Importing data using built-in functions
09:16 -
Importing data using readr package
07:56 -
Reading Writing Excel Worksheets
06:28 -
Reading Writing Native Data File
04:46 -
Loading built-in 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, Multi-period Line Plot, Line Plot with Points, Multi series chart with legend
-
Create Line Plot
03:24 -
Line Type and Width
12:48 -
Multi-period 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
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LevelAll Levels
-
Duration55 hours 30 minutes
-
Last UpdatedJanuary 1, 2023
Hi, Welcome back!
Material Includes
- 55 hours of digital content
- On-demand 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