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Reasons to Learn R Programming Language for a Successful Career in Data Science

Data Science is the hottest subject on the planet today. Every one of the organizations and businesses that you have known about are utilizing it to take advantage of any scenario. 

Data Science’s primary concern is to sort out customer behavior. Professionals who can comprehend the objectives of their clients/customers and foster strategies appropriately are called Data Scientists. This capability has prompted a tremendous interest for Data Scientists and other Data Science professionals in the IT sector. check out this Best Online Data Science Course from a leading learning partner.

It is one of the main reasons why aspirants are looking forward to learning R for Data Science. 

What is Data Science? 

Data Science deals with extracting meaningful insights from a large volume of datasets. A lot of fields converge with Data Science like Statistical Learning, Probabilistic Modelling, Signal Processing, Machine Learning, Data Mining, Data Visualization, Pattern Recognition, etc. The data is cleansed, processed and then analyzed to extract insights that will help in solving a lot of problems related to organization and business operations. 

For instance, Organizations like e-Commerce giant Amazon use Data Science to comprehend their customer behaviors. Then they analyze this customer data to predict customers’ purchasing behavior, their likes and dislikes. Along these lines, when they search for a product on the web, they are likewise shown similar or relevant products that they may like. 

Different programming languages used in Data Science


Thanks to the internet revolution, it is one of the most popular programming languages. Because it has a simple and flat learning curve. Python is a high-level, interpreted language that is well known for its very easy-to-read syntax. 

It offers numerous libraries, for instance, Pandas, Numpy, SciPy, and Matplotlib. We can perform several activities using these libraries like Data Analysis, Data Visualization, forecasts, predictions, etc. Python also offers Deep Learning tools using advanced libraries like Tensorflow and Pytorch for Data Scientists and Engineers. 

R Programming 

R is an ideal choice for a Data Scientist for statistical analysis. The only downside to R is that it has a steep learning curve. R offers you more than 10,000 packages for dealing tasks with statistical analysis. R can handle Neural Networks and Linear Algebra. If you wish to become part of the hugely successful R Community of experts. Check out this R Tutorial for Beginners and get started.


Scala supports both functional programming and object-oriented notions. It is a popular choice for utilizing Apache Spark. It is exceptionally famous for taking care of huge volumes of information. One more significant part of Scala is its capacity in performing parallel processing. 


Every Data Scientist has to deal with data sets and for that, they must learn SQL. It is a language that is used for storing data in a relational database and then retrieving it from there. SQL is crucial to update, manipulate, alert, and wrangle data. 


SAS represents Statistical Analysis and is similar to R. This language was created for Predictive Modelling, Business Intelligence, and Data Analytics. It offers numerous libraries for Statistical Analysis and ML.  

Why learn R programming? 

Let’s dig into the top reasons on Why you should learn R Programming: 

Independent Platform

R’s capability in being able to execute on any Operating System like Windows and UNIX, having different hardware/software makes it platform-independent. This makes it easy to use, specifically if you are a novice in the field of Data Science. 

Broad library 

R exceeds the mark of 10,000 built-in packages and modules to get the job done faster in Data Science. These packages could be used for visualizing data, manipulating data, processing it, ML, and performing statistical modeling. 

Also, R is open-source, so you can alter functions and execute your own according to your prerequisites and use case. 

Solid community support

R is upheld by a huge group of community members who constantly support it. In this way, any issues concerning R, you will discover an answer in online communities like StackOverflow. 

Create web applications

With the help of the RStudio and R Shiny packages, you can build web applications. Meanwhile, you can also make intuitive dashboards and insert visualizations. 

Good opportunity 

R language has an immense interest in the tech market. R developers make higher than USD 117,000 annually. In India, they earn an average of INR 500,000 annually. Learning R opens various job positions like: 

  • Data Scientist
  • Database Admin
  • Data Architect
  • Quantitative Analyst
  • Data Analyst
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According to new insights, R might be the leader in programming languages in the Data Science market. As many as 2 million users and counting are utilizing the language across the world. R is considered the most well-known insightful tool in the Data Science field.

Thomas Leishman

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