Complete R Programming for Data Science

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This bestselling Complete R Programming for Data Science has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Complete R Programming for Data Science is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.

The Complete R Programming for Data Science is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.

We know that you are busy and that time is precious, so we have designed the Complete R Programming for Data Science to be completed at your own pace, whether that’s part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.

Course Curriculum

Unit 01: 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?

Unit 02: R and RStudio

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

Unit 03: Introduction to Basics

• Arithmetic with R
• Variable assignment
• Basic data types in R

Unit 04: Vectors

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

Unit 05: Matrices

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

Unit 06: Factors

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

Unit 07: Data Frames

• What’s a Data Frame?
• Creating Data Frames
• Selection of Data Frame elements
• Conditional selection
• Sorting a Data Frame
• Additional Materials

Unit 08: Lists

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

Unit 09: Relational Operators

• Equality
• Greater and Less Than
• Compare Vectors
• Compare Matrices
• Additional Materials

Unit 10: Logical Operators

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

Unit 11: Conditional Statements

• The IF statement
• IF…ELSE
• The ELSEIF statement
• Additional Materials

Unit 12: 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
• Additional Materials

Unit 13: 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
• Additional Materials

Unit 14: R Packages

• Installing R Packages
• Loading R Packages
• Different ways to load a package
• Additional Materials

Unit 15: 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
• Additional Materials

Unit 16: 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?
• Additional Materials

Unit 17: Useful Functions

• Mathematical functions
• Data Utilities
• Additional Materials

Unit 18: Regular Expressions

• grepl & grep
• Metacharacters
• sub & gsub
• More metacharacters
• Additional Materials

Unit 19: Dates and Times

• Today and Now
• Create and format dates
• Create and format times
• Calculations with Dates
• Calculations with Times
• Additional Materials

Unit 20: Getting and Cleaning Data

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

Unit 21: Plotting Data in R

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

Unit 22: 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
• Additional Materials

Certification

Once you have successfully completed the course, you will be awarded a certificate of completion as evidence of your achievement. You'll get a PDF certificate for FREE, and the hard copy certificate is available for £12 (The shipping cost inside the UK is free, and outside the UK is £9.99).

• This course is for students / professionals who would love to hone skills and knowledge in their chosen area of study.
• This course is aimed at newbies looking to get started to learn in their chosen field as quickly and effectively as possible.

• Eagerness to learn.
• No formal knowledge is required

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