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95% Off R Programming A-Z™: R For Data Science With Real Exercises! Coupon

Join the Comprehensive Course to Learn How to Program in R Deeply, Pick up The Popular R Programming Skills Through Live Examples

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The course titled, “R Programming A-Z™: R for Data Science with Real Exercises!” Is a 10.5-hour course that covers all the important concepts of the R programming language? As the title of the course suggests, the course covers the A-Z of the programming languages of R language.

Udemy is a massive open online course (MOOC), provider. The platform has over 50,000 courses in various disciplines. The courses are taught by professors from elite universities all over the world and professionals who work with some of the top-notch tech tools and have made a name for themselves in the field.

The quality of teachers is given a major importance as the students need to get the proper learning materials. The certificates from Udemy increases one’s resume value as the recruiters are well aware of the fact that Udemy only imparts the current needs using some of the best approach methods.

There are other MOOCs’ too, but very few provide such good service as Udemy provides to its learners. The benefits that one can get by taking up a course from Udemy is a multitude, be it the lesser duration of video lectures with high-quality content, be it the quick response that the students get in the comments section where they post their doubts and queries. Last but not the least, the least price in the market.

Topics that are covered in this course with their explanation

The course runs for the duration of 10. 5 hours and the following topics are covered in this course:

  • How to get started with R?
  • Fundamentals Of R
  • Core principles of programming
  • Matrices in R
  • Data Frames in R
  • Visualization using GGPlot2
  • Solutions to Homework
  • Bonus Solutions

How to Get Started with R Programming Language?


This topic runs for about 40 minutes. This topic covers lectures that help students on how to install the R and R Studio for Mac and Windows Operating Systems. The methods to install software always confuse many. This topic would remove all those confusions that would prevent the students from downloading some malicious software that might induce viruses into the system. The introduction of the R language is also provided under this topic. Few exercises and additional study materials are also provided.

Fundamentals of R

This topic covers some of the concepts that are unique to R like the creation of vector. The vector is an integral part of the function that accepts inputs and performs on it. The use of box brackets is widespread in R. The other programming languages use circular and flower brackets more than the other types of brackets, whereas R uses box brackets the more.

Core principles of programming

The various core principles in programming like the usage of loops, logical statements, variables, and operators are taught in this topic. This has to be understood well before one jumps into the concepts that are unique to R. The packages in R are the extension of the functions that are in use in the other languages.

Matrices in R

The matrices are an important concept in Statistics. The data in statistics are obtained in the form of rows and columns only as they are the values of the different parameters that are obtained as a part of conducting surveys or the historical data like the histogram. The matrices can have any number of rows and columns.

The limited number of rows and columns can be operated by manual calculations. A little bigger number in the number of rows and columns can be calculated using the scientific calculator. Still, the time consumed was large only. Thus, the R has this specialized operator functions on Matrices that performs operations quick.

There are some functions in R that helps even to name the dimensions of the matrix. The rows can be given a name and the columns as well. The answer that has been obtained can be visualized using plots. The plotting is another good feature in R.

Data Frames in R

When Speaking of Data Sciences and Data Analytics using R, this concept comes into action. So far, one has read about the functions and the packages in R that complement the statistical calculation of data. The concept of Data Frames explains how R plays a vital role in Data Sciences and Data Analytics.

The Data Frames are used to import the data that has been in any forms of extension files. The $ sign is the main aspect of the functions of Data Frames. The data thus obtained as input is scattered and it is not in a state that can be analyzed.

One has to perform operations like filtering, sorting, etc., the vector function is used to obtain the input. There are functions like trim to perform operations to provide neat data that can be plotted. The merging of data is also possible.

Visualization using GGPlot2

The GGPlot2 is an advanced visualizing tool that is used in R language. The GGPlot2 is used to transform statistical data using some advanced and new concepts like Facets, Co-ordinates, Layer Plotting, etc., this kind of visualization is used these days to provide the movie ratings.

A mass survey or polling that is conducted will have data inputs in the form of a histogram and other graphical representations. The values that are obtained in the form of graphs are mapped and transformed that they can be plotted and visualized. The GGPlot2 is an advanced tool that provides excellent visualization.

Solutions to Homework

This section holds the answers to the questions that have been given as assignments in the sections mentioned above.

Bonus Solutions

There are also some concepts that one gets a bonus while purchasing this course.

Benefits Derived From This R Course:

The following are few of the benefits that one derives from this course.

  • Covering of all the important concepts in the shortest possible time.
  • Hands on the real-life problems as test cases that help the learner to put the use of his knowledge even better and to grasp easily.
  • Excellent teaching methodology
  • Use of supplementary sources


R – A throwback

The R is a language that is used for statistical computing and graphical representation of data. Before one starts to learn R, one should know some of the basic concepts that are used in programming. The logical thinking is the most important factor to be mastered to learn R. Robert Gentleman, and Ross Ihaka were the ones who developed the R language at the University of Auckland, New Zealand.

The R can be downloaded for free of cost and be supported on many operating systems like Linux, Windows, etc., the language was developed at the Department of Statistics, University of Auckland. There rose a situation where the government of New Zealand, as well as the firms in New Zealand, needed a good tool to perform statistical analysis on the data and to provide insights for the development. One can only develop by having an account of the statistical data. This language was solely developed keeping this aspect of analyzing and reporting.

R and Data Science

R is the highly preferred languages of Data Scientists. It is used to provide a solution to critical problems in businesses. R is taught in Universities but not in every University. The clear and lucid presentation of concepts in R is provided by this course from Udemy. The course titled, ” R Programming A-Z™: R For Data Science With Real Exercises!”, serves as a boost to those who wish to learn R and make a career for themselves in the area of Data Analytics and Data Sciences.

First of all, what are Data Science and Data Analytics and why is it one of the highly paid jobs?

The ones who analyze and provide solutions to some of the most complex problems are always paid high for ages. The times have changed where the Data has taken over the world in all areas, be it transportation, finance, economics. There are very few areas where the quantity of data generated is less. It is not a simple task to handle huge voluminous data, and this is one of the few reasons why these jobs are paid high.

Why is there this buzz over the learning of languages like R for Data Sciences and Data Analytics?

There are very few languages that are devoted towards statistics as well as storing/analysis. The R performs these tasks to the best that is unparalleled with any other programming languages. There are very few languages that suit the needs of analyzing the data effortlessly. This is the reason why there this buzz over the learning of languages likes R for Data Sciences and Data Analytics

R, Data Sciences, Data Analytics

These terms would not seem alien to those who are constantly in touch with the tech buzzwords. The ones who have a brief stint with the tech sector already know the value that one would enjoy by the learning of languages like R that complements Data Sciences and Data Analytics.

R and Statistics

Statistics is one of the oldest forms of sciences. The statistics have gained a lot of momentum, especially after the globalization and liberalization era. The quantity and the variety of jobs have increased. The number of job seekers has increased. The different types of jobs have come into the market. When there is a huge, sudden influx of jobs, there arises a need to create a database to store all the data to analyze the current situation and to predict the prospects.

The Statistical analysis department of every firm, every country is infested with the task of working on statistical data and derive useful insights out of it. This was done manually earlier usually calculators to perform calculations. Later came in the use of technology, the Data Base Management Systems, Spreadsheets came into action. When the data size grew, the manual calculations and the simple tech tools were no longer able to manage the data and provide accurate results. This gave the need for the development of languages like R.

Now, in this century where state data is ruling the world, R comes to the rescue.

Methods by which R solves Statistical problems:

There are many inbuilt functions in the R packages. The R package has the functions that can be used to solve the statistical problems.

Salient Features of the R Language Course:

The following are some of the salient features of the course:

  • 10.5 hours of interrupted video lectures
  • Certificate provided on the completion of a course that includes listening and recording of the video lectures and taking the assignments that are made available on the portal.
  • Supplementary study material apart from the video lectures that help the candidate to learn more about this concept.
  • The downloadable PDF material that holds the syntax of the language R. The built-in functions, the packages list is given clearly.
  • Enhances anytime, anywhere learning. Can be read on any digital electronic device with internet connection with a specified minimum amount of RAM capacity and the speed of the processor system used. The android phones, the electronic devices can be used.
  • The course once bought by paying a certain amount can be accessed for a lifetime. The course never gets expired or doesn’t throw a situation where the user isn’t able to access the lecture videos anymore.

Who can take up this course?

  • Complete beginners who want to learn from scratch
  • The intermediate learners familiar with the basic terms and wish to get a broader and deeper understanding of the topic
  • The ones who already mastered many of the concepts and are willing to learn what they had missed out learning and to implement the current trends

Tips: You can refer to a simple video guide to get the Udemy coupon code.

Thus, the language is one of the highly demanded in the jobs in the market. It is only a great choice if one prefers to take up this course without fail. There are very few courses that cover the in-depth concepts so well that too at much less prices. By using the R Programming A-Z™: R For Data Science With Real Exercises! coupon at checkout, you can generate BIG savings up to 95% discount.

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