Programming languages form the foundation of the Information Technology and Data Science industries. Software Developers and Data Scientists use different programming languages to build innovative applications for multiple industries, including healthcare, education, IoT, banking & finance, logistics, etc.
Since software applications make almost every aspect of our lives more convenient, coding skills are among the most valuable and top-paying skills in IT, Web Design, Data Analytics, Cybersecurity, Business Intelligence, and AI & ML.
While there are tons of programming languages out there, some languages are more popular than others. These languages not only enjoy a vast fanbase but are also backed by active community support.
In this post, we’ll take a look at the top programming languages of the future. So, if you want to know which programming language you should choose for upgrading your professional value, stick with us to the end!
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Top Programming Languages of the Future
When talking about the best programming languages, Python takes the top rank in all its crowning glory. Python is immensely popular among developers and Data Science experts because of its simplicity and versatility.
With an easy learning curve and English-like syntax, Python is a beginner-friendly language. Furthermore, Python has excellent library support for a wide range of coding requirements. For example, Python libraries like Django and Flask are ideal for web development, whereas TensorFlow, Keras, and SciPy are best for Data Science applications. Read more on why python is so popular with developers
You can use Python to develop web & desktop applications, GUI-based desktop applications, ML models, network servers, and so much more. Python’s broad ecosystem of libraries, modules, and frameworks makes application development super easy. It is the backbone of many industry giants like Facebook, Twitter, Pinterest, SurveyMonkey, etc.
R is a dynamic, array-based, multi-paradigm programming language launched back in 1993. It is compatible with all the major operating systems, including macOS, Linux, and Windows. The unique aspect of R is that it doubles up as an environment for statistical computing and graphics. The R environment is an integrated suite of software tools designed for data manipulation, statistical calculation, and graphical display. Read more on career opportunities in R.
R is highly extensible and offers a host of statistical (linear/non-linear modelling, time-series analysis, regression, classification, clustering, etc.) and graphical methods. Being a multi-paradigm language, R supports object-oriented, imperative, functional, and procedural programming paradigms.
Like Python, R comes with an impressive range of libraries like ggplot, tidyr, leaflet, etc. R’s scalable qualities and capacities for statistics and data visualisation are what makes it a favourite of developers and Data Scientists.
Java is the unrivalled organisation king when it comes to server-side application development. It is a class-based, object-oriented programming language used for building software products, mobile applications, web applications, games, web servers, and application servers. Java has long been the leading choice for Android app development. Today, Java is also quite popular among Big Data Engineers who use it to develop Big Data ecosystems.
Java libraries, like JSTAT, Deeplearning4j, JavaML, Weka, ADAMS, Mahout, and RapidMiner, are excellent for ML development. Big names like Uber, Airbnb, Google, Netflix, Amazon, and Spotify use Java in their tech stack.
Read more: Java Project Ideas & Topics
Developed by Microsoft, C# is a general, flexible, and open-source, object-oriented programming (OOP) language. It is primarily used for backend development, game development, web/desktop applications, and mobile application development for Windows phones. It runs on the .NET framework.
C# is widely preferred thanks to its ease-of-use and well-built architecture. It has a dedicated .NET Core machine learning platform – ML.NET – to cater to Machine Learning development needs. There’s also Accord.NET and ML-Agents that allows .NET developers to develop unique ML applications.
C++ is a general-purpose, cross-platform programming language developed by Bjarne Stroustrup as an extension of C. As a result, C++ combines the features of OOP, imperative, and generic programming languages. It offers developers a high level of control over memory and system resources. Speed and efficiency are the two core features of C++ that allow developers to design and build high-performance applications.
C++ is used for developing operating systems, embedded systems, and Graphical User Interfaces (GUIs). Since it is portable, C++ can help build applications that can adapt to multiple platforms/environments. For Machine Learning, C++ has designated ML repositories like Turi Create, TensorFlow, and LightGBM.
Kotlin has a relatively easy-to-learn structure, and apart from Android development, it can be used for web development, desktop app development, and server-side development. Kotlin is concise, safe, and tool-friendly (you can bundle it with any Java IDE or even build via the command line).
Also Read: Highest Paying Programming Language in India
Scala allows developers to easily access JVM features and Java libraries to build applications for various use cases, ranging from web applications to complex ML models. It is used by companies like LinkedIn, AT&T, eBay, and Bloomberg.
Swift is a compiled, general-purpose, multi-paradigm programming language developed by Apple as an upgrade over Objective-C. Swift operates in collaboration with Apple’s Cocoa and Cocoa Touch frameworks. Swift can readily interoperate with the already existing pool of Objective-C code.
With a neat and cohesive syntax, Swift boasts of being a beginner-friendly language. It is a highly expressive and enjoyable scripting language that lets you experiment with the code and view the real-time results. By combining type inference with a modern, lightweight syntax, Swift allows developers to express complex ideas clearly and concisely.
It helps if you have the knowledge and mastery over multiple programming languages in the modern competitive market. As these ten languages have a wide range of industry applications, they often garner high salary packages and promise commendable career growth. What’s interesting to note is, coding skills are valued by companies and organizations worldwide. Thus, if you master at least two to three programming languages, you can find job opportunities in established institutions all over the world.
Now that you know which are the Top programming languages in the job market, you can upgrade your skillset to include at least one (better if multiple!) of these high paying programming languages.
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