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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. Youโll 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 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.
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
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
Whatโs Next
Engine and Coding Environment
Installing R and RStudio
RStudio: A Quick Tour
Arithmetic With R
Variable Assignment
Basic data types in R
Creating a Vector
Naming a Vector
Arithmetic Calculations On Vectors
Vector selection
Selection By Comparison
Whatโs a Matrix
Analyzing Matrices
Naming a Matrix
Adding Columns and Rows To a Matrix
Selection of Matrix Elements
Arithmetic with Matrices
What is Factor
Categorical Variables and Factor Levels
Summarizing a Factor
Ordered Factors
Whatโs a Data Frame
Creating a Data Frame
Selection of Data Frame Elements
Conditional Selection
Sorting a Data Frame
Why Would You Need Lists
Creating Lists
Selecting Elements From a List
Adding more data to the list
Equality
Greater and Less Than
Compare Vectors
Compare Matrices
AND, OR, NOT Operators
Logical Operators with Vectors and Matrices
Reverse the result: (!)
Relational and Logical Operators Together
The IF Statement
IFโฆELSE
The ELSEIF Statement
Full Exercise
Write a While Loop
Looping With More Conditions
Break: Stop the While Loop
Whatโs 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
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
Installing R Packages
Loading R Packages
Different Ways To Load a Package
What Is Lapply and When Is Used.
Use Lapply With User-Defined Functions
Lapply and Anonymous Functions
Use lapply With Additional Arguments
What is Sapply
How to Use Sapply
Sapply With Your Own Function
Sapply With a Function Returning a Vector
When Canโt sapply Simplify.
What is Vapply and Why is it Used.
Mathematical Functions
Data Utilities
Grepl & Grep
Metacharacters
Sub & Gsub
More Metacharacters
Today and Now
Create and Format Dates
Create and Format Times
Calculations with Dates
Calculations with Times
Get and Set Current Directory
Get Data From the Web
Loading Flat Files
Loading Excel files
Base Plotting System
Base plots: Histograms
Base plots: Scatterplots
Base plots: Regression Line
Base plots: Boxplot
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
Accredited by
Tutor Support
Course Access
374 Minutes
CPD UK & QLS
Included
1 Year
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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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 learnerโs ability to learn new things, diversify their skills, and expand their horizons.
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