Programming Languages That Data Scientists Should Master

Posted by Kapil Devang on December 5th, 2019

Today, the demand for data scientist in every industry is growing at a rapid speed. If you aim to develop your business, then it is extremely important that you assess the data that you collect. And data scientist require the skills and the tools so as to enable you to derive better results with your gathered information. For this, one needs to learn data science.

According to the latest report, it has been proved that the demand data scientist will increase by 28% by 2020 and with that, nearly 3 million jobs will be opened for data science professionals.  As machine learning is advancing, thus, data science course is gaining more popularity. Thus, in order to become a data scientist, it is necessary that you gain command on at least one programming language.

Here are some of the top programming languages that a data scientist should master for getting bright future:

Python: It is a popular, general purpose, dynamic and widely used language in the data science industry. It is one of the easiest programming languages to learn and read. It combines with the capacity to create interface with high-performance algorithms that are either written in C or FORTRAN. Also, the demand of data science professionals with python skills are increasing significantly.

R: It is an open source language that is supported by the R Foundation for Statistical Computing. The R skills are in high demand today in the machine learning and data science. This language provides many statistical models and a number of analysts which have composed their applications in R.

Java: Like python, Java is also a general purpose language that runs on JVM or Java Virtual Machine. Most of the organizations use this programming language to create backend systems and desktop/mobile/web applications. It is an Oracle-supported computing system that enhances portability between platforms.

SQL: SQL or Structured Query Language is one of the most popular languages in the field of data science. This programming language is used for querying and editing the information that is stored up in a relational database.

Julia: It is a high-level dynamic programming language that is designed to address the requirements of high-performance numerical analysis and scientific computing. Julia is a new language that is capable of general purpose programming. If you’re aware of the Python language, then Julia is the next programming language to learn.