Top Programming Languages that every Data Scientist should Know.

In every industry, the demand for data scientists is increasing widely. For every business development, there is a need to assess the data you collect. The Data Scientist needs both the best tools and excellent skill set to enable you to produce better results with your information.

Data Scientist is the most excellent job in the US for the last three years. The demand for data scientists’ jobs will increase by 28% by 2020, nearly three million job openings are there for data science professionals.

With the improvement of machine learning, data science is achieving more popularity. You must learn at least one programming language to become a data scientist. Now, let’s take a look at the top programming languages of a data scientist which they should expertise. You can also join the Data Analytics Course in Chennai to gain expertise in the tools and techniques essential for data science, positioning yourself for success in this rapidly growing field.


Python is a popular general-purpose, dynamic language. It is a broadly used language within the Data Science field and referred to as the easiest programming language to read and learn. It combines fast improvement with the ability to interface with high-performance algorithms written in Fortran or C. It becomes the best programming language for open data science.

With the improvement of technologies such as machine learning, artificial intelligence, and predictive analytics, the experts with Python skills are rising significantly. It is extensively used in Scientific computing, Data mining, Web development, and others.


R Programming is an open-source language and it is the most often used tool. It is a software background for graphics and analytical computation, supported by the R Foundation for Statistical Computing. This skill has a high demand for recruiters in Data Science and Machine learning.

R presents many statistical models, and various analysts have designed their applications in R. R is the topper of open statistical analysis, and there is a clear focus on statistical models that have been designed utilizing R. The public R combination contains more than 8000 networks contributed packages. RStudio, Microsoft, and Several organizations provide business support to R-based computing.


Java is a popular, general-purpose language, that runs on the Java Virtual Machine (JVM). A number of MNC organizations use this language to build a backend system and mobile/desktop/web applications. It is an Oracle-supported computing system that allows portability between platforms.

The need for Java skills is increasing, It has been called a pillar of the organization programming stack. Java is demanded especially for Software engineers, Software architects, and DevOps engineers.


SQL (Structured Query Language) is the most common programming language among the data science field. SQL is used for editing and querying the data stored in a relational database and also used for storing and recovering data for decades. It is used in maintaining especially a large database, minimizing the turnaround time for online requests by its fast processing time. Learning SQL skills can be the biggest benefit for Data Science and Machine Learning professionals.

If you want to be a Data Scientist, choose a career and gain more knowledge in Data Science. Refer to this blog for more about What Future Scope of Data Science and a Data Scientist?

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