R Programming Complete Certification Training

A warm welcome to the R Programmingcourse by Uplatz.

R is a programming language that provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible.

While there is something called the S language which is often the vehicle of choice for research in statistical methodology, on the other hand R provides an Open Source route to participation in that activity. R is nothing but an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either on-screen or on hardcopy, and a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

R can be considered as an integrated version of a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. This programming language was named R, based on the first letter of first name of the two R authors (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell Labs Language S.

This R Programming course by Uplatzis designed for software programmers, statisticians and data miners who are looking forward for developing statistical software using R programming. Even if you are a beginner, this R course is the perfect place to start. If you are trying to understand the R programming language as a beginner, this R Programming course will provide you enough understanding on almost all the concepts of the language from where you can take yourself to higher levels of expertise. This R tutorial will provide you an opportunity to take a deep-dive into R programming and build your R skills from scratch. To get the most out of the R programming training, you would need to practice as you proceed with the tutorials.

After successful completion of the R Programming training course you will be able to:

• Master the use of the R and RStudio interactive environment

• Expand R by installing R packages

• Explore and understand how to use the R documentation

• Read Structured Data into R from various sources

• Understand the different data types in R

• Understand the different data structures in R

• R programming constructs – variables, functions, string manipulation, loops, etc.

• Conduct decision-making using R

• Able to do Data and file management in R

• Packages in R

• Plotting and Visualization in R

• and more…

R Programming – Course Syllabus

1. Fundamentals of R Language

• Introduction to R

• History of R

• Why R programming Language

• Comparison between R and Python

• Application of R

2. Setup of R Language

• Local Environment setup

• Installing R on Windows

• Installing R on Linux

• RStudio

• What is RStudio?

• Installation of RStudio

• First Program – Hello World

3. Variables and Data Types

• Variables in R

• Declaration of variable

• Variable assignment

• Finding variable

• Data types in R

• Data type conversion

• R programs for Variables and Data types in RStudio

4. Input-Output Features in R

• scan() function

• readline() function

• paste() function

• paste0() function

• cat() function

• R Programs for implementing these functions in RStudio

5. Operators in R

• Arithmetic Operators

• Relational Operators

• Logical Operators

• Assignment Operators

• Miscellaneous Operators

• R Programs to perform various operations using operators in RStudio

6. Data Structure in R (part-I)

• What is data structure?

• Types of data structure

• Vector

  – What is a vector in R?

  – Creating a vector

  – Accessing element of vector

  – Some more operations on vectors

  – R Programs for vectors in RStudio

• Application of Vector in R

• List

  – What is a list in R?

  – Creating a list

  – Accessing element of list

  – Modifying element of list

  – Some more operations on list

• R Programs for list in RStudio

7. Data Structure in R (part-II)

• Matrix or Matrices

  – What is matrix in R?

  – Creating a matrix

  – Accessing element of matrix

  – Modifying element of matrix

  – Matrix Operations

• R Programs for matrices in RStudio

• Application of Matrices in R

• Arrays

  – What are arrays in R?

  – Creating an array

  – Naming rows and columns

  – Accessing element of an array

  – Some more operations on arrays

• R Programs for arrays in RStudio

8. Data Structure in R (part-III)

• Data frame

  – What is a data frame in R?

  – Creating a data frame

  – Accessing element of data frame

  – Modifying element of data frame

  – Add the new element or component in data frame

  – Deleting element of data frame

  – Some more operations on data frame

• R Programs for data frame in RStudio

• Factors

  – Factors in R

  – Creating a factor

  – Accessing element of factor

  – Modifying element of factor

• R Programs for Factors in RStudio

• Application of Factors in R

9. Decision Making in R

• Introduction to Decision making

• Types of decision-making statements

• Introduction, syntax, flowchart and programs for

  – if statement

  – if…else statement

  – if…else if…else statement

  – switch statement

10. Loop control in R

• Introduction to loops in R

• Types of loops in R

  – for loop

  – while loop

  – repeat loop

  – nested loop

• break and next statement in R

• Introduction, syntax, flowchart and programs for

  – for loop

  – while loop

  – repeat loop

  – nested loop

11. Functions in R

• Introduction to function in R

• Built-in Function

• User-defined Function

• Creating a Function

• Function Components

• Calling a Function

• Recursive Function

• Various programs for functions in RStudio

12. Strings in R

• Introduction to string in R

  – Rules to write R Strings

  – Concatenate two or more strings in R

  – Find length of String in R

  – Extract Substring from a String in R

  – Changing the case i.e. Upper to lower case and lower to upper case

• Various programs for String in RStudio

13. Packages in R

• Introduction to Packages in R

• Get the list of all the packages installed in RStudio

• Installation of the packages

• How to use the packages in R

• Useful R Packages for Data Science

• R program for package in RStudio

14. Data and File Management in R

• Getting and Setting the Working Directory

• Input as CSV File

• Analysing the CSV File

• Writing into a CSV File

• R programs to implement CSV file

15. Plotting in R (Part-I)

• Line graph

• Scatterplots

• Pie Charts

• 3D Pie Chart

16. Plotting in R (Part-II)

• Bar / line chart

• Histogram

• Box plot

Rating Distribution

• 1 stars: 13 votes
• 2 stars: 14 votes
• 3 stars: 41 votes
• 4 stars: 94 votes
• 5 stars: 80 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!