R Programming from Scratch for Data Science - Step by step
4.2 (46 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,317 students enrolled

R Programming from Scratch for Data Science - Step by step

Learn R Language (Data Science) for beginners : Become Data Scientist
4.2 (46 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
7,317 students enrolled
Created by Happy Learning
Last updated 4/2020
English
English [Auto-generated]
Current price: $13.99 Original price: $19.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 5.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
What you'll learn
  • Learn R programming
  • Learn different ways to draw Graphs and analyze graphs
Course content
Expand all 90 lectures 05:21:44
+ Introduction
9 lectures 40:39
Install R on Windows
03:37
Hello World in R
06:40
Editors in R
04:51
R Studio Installation in Windows
01:55
R Studio Installation in Linux
02:13
R Studio Overview
07:50
+ Variables and Operators in R
11 lectures 46:45
Variable and Naming Convention
04:25
Assign Variable
02:59
Environment and Variables
06:55
Operators
01:02
Arithmetic Operators
06:56
Special Numbers : Inf, NaN, NA
06:08
Logical Operators
03:27
Vectorized Operations
02:23
Types of Vectorized Operations
09:18
Summary
02:13
+ R Data Structure - 1
8 lectures 45:09
Data Structures in R
03:30
Atomic Vector
11:15
Common Operations on Atomic Vectors
09:05
Factor
06:45
List
06:07
Common Operation on Lists
05:37
Summary
02:03
+ R Data Structure - 2
7 lectures 35:21
Outline
00:27
Data Frame
06:49
Common Operation on Data Frames
08:40
Matrix
06:38
Common Operation on Matrices
05:41
Array
04:53
Summary
02:13
+ Functions in R
12 lectures 34:38
Outline
00:55
Functions Overview
06:57
Function Components
01:18
Function Naming Guidelines
01:21
Argument Matching
02:05
Arguments With Default Values
02:59
Additional Arguments Using Ellipsis
04:31
Lazy Evaluation
03:35
Multiple Return Values
02:29
Functions as Objects
03:45
Anonymous Function
02:35
Summary
02:08
+ Flow Control in R
14 lectures 40:33
Outline
01:00
If Statement
04:49
If-Else
02:33
Multiple If-Else
04:07
Switch
05:38
Vectorized If
04:56
Repeat
01:56
Repeat With Break
02:09
Repeat With Next
02:25
While
02:47
For Loop
02:26
Apply
01:50
Functions in Apply Family
00:45
Summary
03:12
+ Packages in R
7 lectures 25:51
Outline
00:27
About R Package
04:10
Load R Package
01:21
Demo: Load R Package
05:36
Install R Package
08:43
Manage R Package
03:46
Summary
01:48
+ Import Data in R
11 lectures 37:25
Outline
00:55
Working Directory
03:35
Import CSV Files
04:37
Import Table
05:36
Import from URL
03:31
Import XML Files
02:54
Import Excel Files
04:43
Import Other File Types
01:46
Import Built-In Datasets
02:59
Import from Database
05:09
Summary
01:40
+ Exploring Data With R
11 lectures 15:23
Outline
00:46
Types of Data
02:40
Overall Structure
00:31
Example Dataset
00:51
Demo: Overall Structure
02:14
Analysis of Continuous Data
00:27
Central Tendency (Mean)
01:23
Demo: Central Tendency (Mean)
01:00
Central Tendency (Median)
01:47
Central Tendency: Why Not Sufficient?
01:22
Spread (Range)
02:22
Requirements
  • No technical knowledge required
  • A laptop to learn course and practice exercise
  • Good internet connection
Description

Welcome to the course, R Programming from Scratch

R is a powerful and widely used open source software and programming environment for data analysis. Companies across the globe use R as an essential tool for various types of analysis to get key insights from data and to make key decisions. This course will provide everything you need to know to get started with the R framework, and contains a number of demos to provide hands-on practice in order to become an efficient and productive R programmer. By the end of this course, you will also learn to play with data and to extract key information using various R functions and constructs.

You will learn below:

1. Introduction

2. Installation of R Language

3. Installation of R Studio on Windows and Linux

4. Variable and Operators


Who this course is for:
  • College Grads
  • Job Seekers