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Learning R Programming for Data Science

Learning R Programming for Data Science

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In this course, you will master one of the most powerful tools in the data science toolkit. Through a combination of theoretical concepts and practical exercises, you will learn the fundamentals of R programming language and its application in data analysis, visualisation and statistical modelling.

What will you learn from this course?

  • Gain comprehensive knowledge about R programming
  • Understand the core competencies and principles of R programming
  • Explore the various areas of R programming
  • Know how to apply the skills you acquired from this course in a real-life context
  • Become a confident and expert data analyst

Learning R Programming for Data Science Course

Master the skills you need to propel your career forward in R programming. This course will equip you with the essential knowledge and skillset that will make you a confident data analyst and take your career to the next level. This comprehensive R programming for data science course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this R programming for data science course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career.

This comprehensive course will teach you the theory of effective R programming practice and equip you with the essential skills, confidence and competence to assist you in the R programming industry. Youโ€™ll gain a solid understanding of the core competencies required to drive a successful career in R programming. This course is designed by industry experts, so you’ll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for data analyst or for people who are aspiring to specialise in R programming.

Enrol in this learning R programming for data science course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates.

Who is this Course for?

This comprehensive learning R programming for data science course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this R programming can also take this course.

Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector.

Entry Requirements

This learning R programming for data science course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection.

Assessment

This learning R programming for data science course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%.

Recognised Accreditation

 

CPD

CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field.

QLS

The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries.

Course Curriculum

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

Whatโ€™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

Whatโ€™s a Matrix

Analyzing Matrices

Naming a Matrix

Adding Columns and Rows To a Matrix

Selection of Matrix Elements

Arithmetic with Matrices

Factors

What is Factor

Categorical Variables and Factor Levels

Summarizing a Factor

Ordered Factors

Data Frames

Whatโ€™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 Lists

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

IFโ€ฆELSE

The ELSEIF Statement

Full Exercise

Loops

Write a While Loop

Looping With More Conditions

Break: Stop the While Loop

Whatโ€™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 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 Canโ€™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 Ccomponent: Relocate()

Rows Component: Filter()

Rows Component: Slice()

Rows Component: Arrange()

Rows Component: Rowwise()

Grouping of Rows: Summarise()

Grouping of Rows: Across()

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Course info

Duration

Duration

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Tutor Support

Tutor Support

Course Access

Course Access

374 Minutes

CPD UK & QLS

Included

1 Year

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FAQs

CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world.

Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards.

For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days.

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Yes, you can pay via instalments at checkout.

No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learnerโ€™s ability to learn new things, diversify their skills, and expand their horizons.

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