Top 10 Programming Languages that Data Scientists Should Learn in 2022 – Analytics Insight



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December 25, 2021

Programming Languages

Programming languages have been cited as the most important skills for data scientists

Data science sits at the intersection of analytics and engineering, so a combination of mathematical skills and programming expertise is relevant. Data scientists with software skills are more desirable candidates. Programming has been cited as the most important skill for a data scientist. A data scientist with a software background is a more self-sufficient expert who does not need outside resources to work with data. Today, it is practically impossible to lead a life without technology. With that being said, one of the most important aspects of technology is programming. Programming languages are computer languages that are used by programmers (developers) to communicate with computers. This article lists the top 10 programming languages that data scientists should learn in 2022. 

Javascript

In this tech-driven era, where computers play a very important role, it is almost impossible to say that there is a developer not using Javascript in some way. Javascript is a high-level programming language that is one of the core technologies of the World Wide Web. The main purpose of Javascript was for front-end development, but now, it can also be used for back-end development, especially after the advent of NodeJS. Javascript is surely one of the best programming languages to learn for data scientists in 2022. 

Java

Built-in 1991 by James Gosling, Mike Sheridan, and Patrick Naughton as the language ‘Oak’, Java was the first language to have a big global impact. One of the most widely used programming languages, Java is used as the server-side language for most back-end development projects, including those involving big data and Android development. Java is also commonly used for desktop computing, other mobile computing, games, and numerical computing.

Scala

Scala is an extension of Java, a language associated strongly with data engineering, with interoperability thanks to Java bytecode compiling and running on Java Virtual Machine. Built as a response to perceived problems in Java, it’s a newer, more elegant language. Scala enables high-performance frameworks for handling siloed data, perfect for enterprise-level data science.

Python

Python is one of the most popular programming languages today and will continue to be so in 2022 and beyond. It is a high-level, general-purpose programming language that is easy for beginners to learn because of its readability with support for many useful libraries and web frameworks. This coding language demonstrates a 2.17% rise over its previous positions, which contrasts with a decline for Java over the same period.

R

R is one of the computer programming languages used in the world of data science. Ruby is a well-known programming language, especially popular among startups. Such high flyers as Airbnb, Twitch, and GitHub were powered by Ruby. Its demand is bolstered on Ruby on Rails, which is a full-stack web application framework that fuels Ruby.  

SQL

SQL (Structured Query Language), as the name suggests, allows programmers to query and manipulate databases. This programming language stands for the ability to locate and retrieve data from a database, as well as update, add or remove records (i.e to manipulate databases). SQL finds a huge application in business and database management.

C++

Perhaps one of the most shocking answers that one can expect in this article is C++. C++ finds use in analytics, research as well as in-game development. The popular game development engine – the Unreal Engine – uses C++ as the scripting language for all of the functionality one can define while building a game. C++ also finds extensive use in software development.

Julia

Julia is another new entrant on this list. With less than 10 years since its initial, it lacks maturity despite being among newer languages. Julia is growing in popularity among data scientists that work in the high-performance computing environment. It not only offers fast development speed but also produces applications that run similarly to those created on low-level languages.

MATLAB

MATLAB is a programming language and environment specific to mathematical and statistical computing. It offers built-in tools for dynamic visualizations and offers users a deep learning toolbox that transitions well. It allows you to ease challenging mathematical processes.

HTML

HTML is a popular platform for creating cross-platform and cross-browser applications and games, according to game developers. It can also be utilized interchangeably with JavaScript. HTML is a simple programming language and does not need an extensive programming understanding of algorithms, making it a prominent choice among game designers.

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Top 10 Programming Languages that Data Scientists Should Learn in 2022 – Analytics Insight



by

December 25, 2021

Programming Languages

Programming languages have been cited as the most important skills for data scientists

Data science sits at the intersection of analytics and engineering, so a combination of mathematical skills and programming expertise is relevant. Data scientists with software skills are more desirable candidates. Programming has been cited as the most important skill for a data scientist. A data scientist with a software background is a more self-sufficient expert who does not need outside resources to work with data. Today, it is practically impossible to lead a life without technology. With that being said, one of the most important aspects of technology is programming. Programming languages are computer languages that are used by programmers (developers) to communicate with computers. This article lists the top 10 programming languages that data scientists should learn in 2022. 

Javascript

In this tech-driven era, where computers play a very important role, it is almost impossible to say that there is a developer not using Javascript in some way. Javascript is a high-level programming language that is one of the core technologies of the World Wide Web. The main purpose of Javascript was for front-end development, but now, it can also be used for back-end development, especially after the advent of NodeJS. Javascript is surely one of the best programming languages to learn for data scientists in 2022. 

Java

Built-in 1991 by James Gosling, Mike Sheridan, and Patrick Naughton as the language ‘Oak’, Java was the first language to have a big global impact. One of the most widely used programming languages, Java is used as the server-side language for most back-end development projects, including those involving big data and Android development. Java is also commonly used for desktop computing, other mobile computing, games, and numerical computing.

Scala

Scala is an extension of Java, a language associated strongly with data engineering, with interoperability thanks to Java bytecode compiling and running on Java Virtual Machine. Built as a response to perceived problems in Java, it’s a newer, more elegant language. Scala enables high-performance frameworks for handling siloed data, perfect for enterprise-level data science.

Python

Python is one of the most popular programming languages today and will continue to be so in 2022 and beyond. It is a high-level, general-purpose programming language that is easy for beginners to learn because of its readability with support for many useful libraries and web frameworks. This coding language demonstrates a 2.17% rise over its previous positions, which contrasts with a decline for Java over the same period.

R

R is one of the computer programming languages used in the world of data science. Ruby is a well-known programming language, especially popular among startups. Such high flyers as Airbnb, Twitch, and GitHub were powered by Ruby. Its demand is bolstered on Ruby on Rails, which is a full-stack web application framework that fuels Ruby.  

SQL

SQL (Structured Query Language), as the name suggests, allows programmers to query and manipulate databases. This programming language stands for the ability to locate and retrieve data from a database, as well as update, add or remove records (i.e to manipulate databases). SQL finds a huge application in business and database management.

C++

Perhaps one of the most shocking answers that one can expect in this article is C++. C++ finds use in analytics, research as well as in-game development. The popular game development engine – the Unreal Engine – uses C++ as the scripting language for all of the functionality one can define while building a game. C++ also finds extensive use in software development.

Julia

Julia is another new entrant on this list. With less than 10 years since its initial, it lacks maturity despite being among newer languages. Julia is growing in popularity among data scientists that work in the high-performance computing environment. It not only offers fast development speed but also produces applications that run similarly to those created on low-level languages.

MATLAB

MATLAB is a programming language and environment specific to mathematical and statistical computing. It offers built-in tools for dynamic visualizations and offers users a deep learning toolbox that transitions well. It allows you to ease challenging mathematical processes.

HTML

HTML is a popular platform for creating cross-platform and cross-browser applications and games, according to game developers. It can also be utilized interchangeably with JavaScript. HTML is a simple programming language and does not need an extensive programming understanding of algorithms, making it a prominent choice among game designers.

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