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Overview

Overview

Grasp the science of R Programming for Data Science and how it relates to launching a lucrative career. Prepare for future R Programming for Data Science needs by looking beyond the ongoing R Programming for Data Science impact with Discover Training’s up-to-date R Programming for Data Science course .

Discover Training’s R Programming for Data Science course gives you a solid foundation in R Programming for Data Science in many settings of human development. With industry expert interviews, you’ll gain a greater understanding of R Programming for Data Science‘s applications and limitations, as well as how it’s already been efficiently used in the field. Discover Training’s R Programming for Data Science course will help you obtain facts and knowledge to strengthen your abilities on both standard R Programming for Data Science techniques.

As you progress through the interactive modules of this online program, you will have a strong grasp of R Programming for Data Science to identify new opportunities for innovation and drive digital growth within your organization. Enrol in the R Programming for Data Science course today and leverage your knowledge tomorrow. 

Description:

Industry professionals developed the content of this online R Programming for Data Science course, combining their expertise and in-depth knowledge. The curriculum was developed by Discover Training to assist you in growing in your current role by providing you with the necessary information and concepts. As you progress through the modules of this course, you’ll learn the fundamentals of  R Programming for Data Science and explore the essential concepts.

Who is this course for?

This R Programming for Data Science course is for you if you want to learn about the revolutionary potential of R Programming for Data Science. Whether you are a newbie or a seasoned veteran, a grasp of challenges that R Programming for Data Science techniques can tackle would benefit anyone working in the R Programming for Data Science sector. This R Programming for Data Science training covers crucial subjects that will help you overcome challenges and improve your practices.

Requirements:

  • Prerequisites: None
  • Age Limit: 16+
  • Gadgets: Smart devices and internet

Certification

Once the R Programming for Data Science course is successfully completed, the learner can obtain the PDF certificate without any cost. The hardcopy version of the certificate is also available for only £9.99. However, anyone ordering the hardcopy certificate from outside the United Kingdom may need to pay an additional delivery charge.

Course Curriculum

Unit 01: Data Science Overview
Introduction to Data Science 00:01:00
Data Science: Career of the Future 00:04:00
What is Data Science? 00:02:00
Data Science as a Process 00:02:00
Data Science Toolbox 00:03:00
Data Science Process Explained 00:05:00
What’s Next? 00:01:00
Unit 02: R and RStudio
Engine and coding environment 00:03:00
Installing R and RStudio 00:04:00
RStudio: A quick tour 00:04:00
Unit 03: Introduction to Basics
Arithmetic with R 00:03:00
Variable assignment 00:04:00
Basic data types in R 00:03:00
Unit 04: Vectors
Creating a vector 00:05:00
Naming a vector 00:04:00
Arithmetic calculations on vectors 00:07:00
Vector selection 00:06:00
Selection by comparison 00:04:00
Unit 05: Matrices
What’s a Matrix? 00:02:00
Analyzing Matrices 00:03:00
Naming a Matrix 00:05:00
Adding columns and rows to a matrix 00:06:00
Selection of matrix elements 00:03:00
Arithmetic with matrices 00:07:00
Additional Materials 00:00:00
Unit 06: Factors
What’s a Factor? 00:02:00
Categorical Variables and Factor Levels 00:04:00
Summarizing a Factor 00:01:00
Ordered Factors 00:05:00
Unit 07: Data Frames
What’s a Data Frame? 00:03:00
Creating Data Frames 00:20:00
Selection of Data Frame elements 00:03:00
Conditional selection 00:03:00
Sorting a Data Frame 00:03:00
Additional Materials 00:00:00
Unit 08: Lists
Why would you need lists? 00:01:00
Creating a List 00:06:00
Selecting elements from a list 00:03:00
Adding more data to the list 00:02:00
Additional Materials 00:00:00
Unit 09: Relational Operators
Equality 00:03:00
Greater and Less Than 00:03:00
Compare Vectors 00:03:00
Compare Matrices 00:02:00
Additional Materials 00:00:00
Unit 10: Logical Operators
AND, OR, NOT Operators 00:04:00
Logical operators with vectors and matrices 00:04:00
Reverse the result: (!) 00:01:00
Relational and Logical Operators together 00:06:00
Additional Materials 00:00:00
Unit 11: Conditional Statements
The IF statement 00:04:00
IF…ELSE 00:03:00
The ELSEIF statement 00:05:00
Full Exercise 00:03:00
Additional Materials 00:00:00
Unit 12: Loops
Write a While loop 00:04:00
Looping with more conditions 00:04:00
Break: stop the While Loop 00:04:00
What’s a For loop? 00:02:00
Loop over a vector 00:02:00
Loop over a list 00:03:00
Loop over a matrix 00:04:00
For loop with conditionals 00:01:00
Using Next and Break with For loop 00:03:00
Additional Materials 00:00:00
Unit 13: Functions
What is a Function? 00:02:00
Arguments matching 00:03:00
Required and Optional Arguments 00:03:00
Nested functions 00:02:00
Writing own functions 00:03:00
Functions with no arguments 00:02:00
Defining default arguments in functions 00:04:00
Function scoping 00:02:00
Control flow in functions 00:03:00
Additional Materials 00:00:00
Unit 14: R Packages
Installing R Packages 00:01:00
Loading R Packages 00:04:00
Different ways to load a package 00:02:00
Additional Materials 00:00:00
Unit 15: The Apply Family - lapply
What is lapply and when is used? 00:04:00
Use lapply with user-defined functions 00:03:00
lapply and anonymous functions 00:01:00
Use lapply with additional arguments 00:04:00
Additional Materials 00:00:00
Unit 16: The apply Family – sapply & vapply
What is sapply? 00:02:00
How to use sapply 00:02:00
sapply with your own function 00:02:00
sapply with a function returning a vector 00:02:00
When can’t sapply simplify? 00:02:00
What is vapply and why is it used? 00:04:00
Additional Materials 00:00:00
Unit 17: Useful Functions
Mathematical functions 00:05:00
Data Utilities 00:08:00
Additional Materials 00:00:00
Unit 18: Regular Expressions
grepl & grep 00:04:00
Metacharacters 00:05:00
sub & gsub 00:02:00
More metacharacters 00:04:00
Additional Materials 00:00:00
Unit 19: Dates and Times
Today and Now 00:02:00
Create and format dates 00:06:00
Create and format times 00:03:00
Calculations with Dates 00:03:00
Calculations with Times 00:07:00
Additional Materials 00:00:00
Unit 20: Getting and Cleaning Data
Get and set current directory 00:04:00
Get data from the web 00:04:00
Loading flat files 00:03:00
Loading Excel files 00:05:00
Additional Materials 00:00:00
Unit 21: Plotting Data in R
Base plotting system 00:03:00
Base plots: Histograms 00:03:00
Base plots: Scatterplots 00:05:00
Base plots: Regression Line 00:03:00
Base plots: Boxplot 00:03:00
Unit 22: Data Manipulation with dplyr
Introduction to dplyr package 00:04:00
Using the pipe operator (%>%) 00:02:00
Columns component: select() 00:05:00
Columns component: rename() and rename_with() 00:02:00
Columns component: mutate() 00:02:00
Columns component: relocate() 00:02:00
Rows component: filter() 00:01:00
Rows component: slice() 00:04:00
Rows component: arrange() 00:01:00
Rows component: rowwise() 00:02:00
Grouping of rows: summarise() 00:03:00
Grouping of rows: across() 00:02:00
COVID-19 Analysis Task 00:08:00
Additional Materials 00:00:00

FAQS

Yes, our course is UK recognised and CPD certified.

You will have 14 days to revoke your Course purchase from your purchase date. Regrettably, refunds are not allowed after your purchase have been approved, and materials have been posted to the student’s dashboard or accessed.

We offer various payment options depending on the country and region of your account. When you wish to acquire a course, you could look at the several payment options:

  • • Go to the course home page and click ‘Take This Course’ after selecting the course you wish to take.
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There are no time constraints for starting or completing any course. You are free to begin any course at any time. Furthermore, as long as your account is in good standing and we own the copyright to the course, you’ll have access to it even after you’ve finished it.

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