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Complete R Programming course: Beginner to Advanced Level

Master R 4.2.2: Learn Data Aggregation, Tidyverse, reshape, tidyr, dplyr, data.table packages and so on!

Course Description

*Learn R Programming (4.2) by Coding Along*

**Learn R 4.2 at your own pace!**

Are you starting you R programming journey? Are you a complete beginner in programming?

This course is suitable for you!

Why learn R using is course?

This course covers all the theory needed for the understanding of writing a well neat R code. The latest version of R and R Studio is used to cover all   the required concepts for everyone who wants to have a career in the fields like:

  • Data Analyst

  • Quantitative Analyst

  • Data Scientists

  • Financial Analysts and many other high paying careers

By the end of this course you will have mastered:

1. The Basics of R

  • R Data Types

  • R for Basic Maths

  • Complicated Arithmetic formulas R

2. Data Structures in R

  • Vectors

  • Matrices

  • Arrays

  • Dataframes

  • Lists

3. Working with Categorical Data

  • What is categorical Data?

  • Factors in R programming – what are factors in r

  • Creating factors

  • Regular expression – grep and gsub functions in r

4. Functions in R

  • Calling R functions

  • Writing R functions

5. if statements

  • Stand-alone statement

  • else if & else statements

  • using if statements in functions

  • nested if statements

  • switch function

6. Loops

  • what is a loop?

  • for loops

  • while loops

  • nested loops

  • using loops within a function

7. The apply family of functions

  • apply function

  • lapply function

  • sapply function

  • tapply function

8. Importing Data into R with tidyverse

  • read a csv file in r

  • read an excel file in r with tidyverse

9. Data Manipulation & Transformation in R

  • Sorting, Appending and Merging

  • Duplicated Values

  • Restructuring with reshape package

  • Melting and Casting

  • Restructuring with tidyr package

  • Gather and spare

  • Data Aggregation

10. dplyr package

  • Sorting

  • Subscripting

  • Merging

  • Aggregation

  • What is the pipe operator in r?

11. data.table package

  • Setting Key & Subscripting

  • Merging & Aggregation

I'm certain you will enjoy this course!

Goals

In this course you will learn:

  • Advanced data analytics with dplyr package
  • Advanced analytics with datatable package
  • How to perform sorting, subscripting, Merging of R Data structures
  • Data Aggregartion using dplyr and data table packages
  • Data Aggregation with aggregate function
  • Data Analysis with Apply family of functions: apply(), sapply(), tapply(), lapply()
  • Importing data into R using tidyverse package
  • Restructuring real datasets with reshape package
  • Restructuring real world datasets with melt and cast functions
  • Restructuring real datasets with tidy package package
  • Restructuring real world datasets with gather and spare functions
  • How to work with categorical data
  • what are factors in R?
  • Regular expression with grep & gsub function
  • if statements: nested in statements
  • How to use the switch function in r
  • Complete explanations of the for loops and while loops using R
  • How to use loops within your own functions
  • How to create, manage and subscript R Data Structures
  • Complete explanation and Application of Vectors, Matrices and Arrays with real datasets
  • Complete explanation and Application of Dataframes and Lists in r
  • Calling R Functions & How to write your own functions
  • R for Complicated mathematics formulae
  • Master R 4.2.2
  • What is the Pipe Operator & How to use it

Prerequisites

  • No prior programming experience required
  • Eager to learn
  • The course only require internet connection for installing the latest version of R & R Studio
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Curriculum

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Complete R Programming course: Beginner to Advanced Level
This Course Includes
  • 7.5 hours
  • 122 Lectures
  • 4 Resources
  • Completion Certificate Sample Certificate
  • Lifetime Access Yes
  • Language English
  • 30-Days Money Back Guarantee

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