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Programming Languages for Data Science

By NIIT Editorial

Published on 28/03/2021

6 minutes

Amongst all the skills that a data scientist is an expert at, coding is rudimentary. Although in and of itself it may not solve a standalone purpose, it allows analysts to implement various applications some of which involve statistical analysis, machine learning, and data processing to name some. There is no one-size-fits-all approach here. It is important to have a stronghold on relevant programming languages, even if some have risen out of obscurity in recent years. Here is a list of trending programming languages that could benefit data scientists immensely in 2021.   


Python Programming


It is arguably one of the most widely used programming languages by data scientists. It is easy to use, open-source and offers a high variety library for developers. Python offers GUI programming support and is integrated and portable at the same time. One of the most striking facets of Python is that you do not have to declare the variable type as the same is dynamically typed. Another reason why the code is low-volume is because Python has a large standard library that makes writing code for minor tasks redundant. 




It is highly regarded by statisticians for purposes of data visualization. This is because it programming language R has graphical capabilities. When it comes to reporting and creating diagrammatic representations, few programming languages come close to R. It also offers 10, 000 different packages and extensions that are specifically required for data science operations. The fact that R uses the concept of distributed computing, makes it process tasks with such an efficiency that is hard to mimic. 




Just like R, JavaScript is also used to create visualizations by data scientists. It was voted as the most preferred language by developers in the latest installment of a StackOverflow survey. With React, a framework based on JavaScript, developers can create interactive packages. Data processing frameworks like Hadoop run on Java which proves its application in regards to processing data. Just like Python, JavaScript offers a wide list of libraries, particularly for machine learning operations. 




It is widely deployed for managing database management systems (DBMS). Systematic Query Language is the most preferred option for data manipulation, data definition, data control, and data query. It integrates easily with scripting languages and allows managing huge volumes of data. While working with relational databases, SQL can be used to retrieve, store and manipulate data. 




Scala was launched in 2003 as an object-oriented programming language that also supports functional programming. It is supported by Java Virtual Machines (JVM) and was introduced as a progressive step over Java improving upon its shortcomings. The acronym Scala stands for scalable language and it is often touted that it was inspired by programming languages like Pizza, Haskell, and Lisp.


Final Thoughts 


Programming aptitude is a prerequisite for going the distance in the data science industry but let it not be a bottleneck. Our history at NIIT proves we have been the bastion for emerging technologies for more than 2 decades. In line with our vision to impart job-ready prerequisites the following state-of-the-art programs are an elusive opportunity to students. Led by a faculty with a proven track record choose from a range of data science courses that prepare you for the sexiest job of the 21st century: 



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