Learning R Programming for Data Science

Beginner to Intermediate R Programming Language Training Course

4.55 (27 reviews)
Udemy
platform
English
language
Other
category
111
students
6 hours
content
Aug 2021
last update
$59.99
regular price

What you will learn

Describe Data Science and Big Data

Identify the importance of Data Science

Describe main tools used in Data Science

Explain steps of a Data Science project

Recognize the main environment and files of RStudio

Perform arithmetic calculations in R

Solve simple data problems using vectors, matrices, factors, data frames, and lists in R

Use Operators and Conditional Statements to perform comparison and controlled-flow data problems in R

Solve data problems using Loops in R

Use base R functions and create user-defined functions in R

Get and clean external data in R

Plot data in R using Base Plotting

Install and use different R Packages

Analyze data using helpful functions in R such as base mathematical functions, Apply family, Regular Expressions, and Dates & Times

Manipulate datasets in R using dplyr package

Description

This course puts the participant in the right path to become a competent Data Scientist by teaching him/her the basics of R Language as one prominent tool in Data Science.

The course starts by introducing Data Science and the steps taken to complete a Data Science project. Then it continues with lectures on various methods and functions of R enabling the participant to start his/her journey towards becoming a Data Scientist with R.

In this course participants will learn how to install and configure R and RStudio. Besides, participants will be able to create various data structures such as Vectors, Matrices, Factors, Data Frames, and Lists. They will solve simple data problems using Operators, Conditional Statements, Loops, base and user-defined functions. Participants will understand and use different data gathering and manipulation methods such as getting and cleaning external files, the Apply family, Regular Expressions, Dates & Times, Base Plotting, and the dplyr package.

Content

Introduction

Introduction

Data Science Overview

Introduction to Data Science
Data Science: Career of the Future
What is Data Science?
Data Science as a Process
Data Science Toolbox
Data Science Process Explained
What's Next?

R and RStudio

Engine and coding environment
Installing R and RStudio
RStudio: A quick tour

Introduction to Basics

Arithmetic with R
Variable assignment
Basic data types in R

Vectors

Creating a vector
Naming a vector
Arithmetic calculations on vectors
Vector selection
Selection by comparison

Matrices

What's a Matrix?
Analyzing Matrices
Naming a Matrix
Adding columns and rows to a matrix
Selection of matrix elements
Arithmetic with matrices

Factors

What's a Factor?
Categorical Variables and Factor Levels
Summarizing a Factor
Ordered Factors

Data Frames

What's a Data Frame?
Creating a Data Frame
Selection of Data Frame elements
Conditional selection
Sorting a Data Frame

Lists

Why would you need lists?
Creating a List
Selecting elements from a list
Adding more data to the list

Relational Operators

Equality
Greater and Less Than
Compare Vectors
Compare Matrices

Logical Operators

AND, OR, NOT Operators
Logical operators with vectors and matrices
Reverse the result: (!)
Relational and Logical Operators together

Conditional Statements

The IF statement
IF…ELSE
The ELSEIF statement
Full Exercise

Loops

Write a While loop
Looping with more conditions
Break: stop the While Loop
What’s a For loop?
Loop over a vector
Loop over a list
Loop over a matrix
For loop with conditionals
Using Next and Break with For loop

Functions

What is a Function?
Arguments matching
Required and Optional Arguments
Nested functions
Writing own functions
Functions with no arguments
Defining default arguments in functions
Function scoping
Control flow in functions

R Packages

Installing R Packages
Loading R Packages
Different ways to load a package

The apply Family - lapply

What is lapply and when is used?
Use lapply with user-defined functions
lapply and anonymous functions
Use lapply with additional arguments

The apply Family – sapply & vapply

What is sapply?
How to use sapply
sapply with your own function
sapply with a function returning a vector
When can't sapply simplify?
What is vapply and why is it used?

Useful Functions

Mathematical functions
Data Utilities

Regular Expressions

grepl & grep
Metacharacters
sub & gsub
More metacharacters

Dates and Times

Today and Now
Create and format dates
Create and format times
Calculations with Dates
Calculations with Times

Getting and Cleaning Data

Get and set current directory
Get data from the web
Loading flat files
Loading Excel files

Plotting Data in R

Base plotting system
Base plots: Histograms
Base plots: Scatterplots
Base plots: Regression Line
Base plots: Boxplot

Data Manipulation with dplyr

Introduction to dplyr package
Using the pipe operator (%>%)
Columns component: select()
Columns component: rename() and rename_with()
Columns component: mutate()
Columns component: relocate()
Rows component: filter()
Rows component: slice()
Rows component: arrange()
Rows component: rowwise()
Grouping of rows: summarise()
Grouping of rows: across()
COVID-19 Analysis Task

Concluding the Course

A message from the instructor

Screenshots

Learning R Programming for Data Science - Screenshot_01Learning R Programming for Data Science - Screenshot_02Learning R Programming for Data Science - Screenshot_03Learning R Programming for Data Science - Screenshot_04

Reviews

Ramon
August 2, 2020
The introductory part is already very good. It introduces the topic in such a way that one would one to complete the course. I will complete this course, The God willing.

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Related Topics

3339588
udemy ID
7/17/2020
course created date
8/29/2020
course indexed date
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