The foundation of the information technology and data science industries is programming languages. Software Developers and Data Scientists use various programming languages to create innovative applications for various industries such as healthcare, education, IoT, banking & finance, logistics, and so on.
Coding skills are among the most valuable and highest-paying skills in professional ghostwriters, IT, Web Design, Data Analytics, Cybersecurity, Business Intelligence, and AI & ML because software applications make almost every aspect of our lives more convenient.
While there are numerous programming languages available, some are more popular than others. These languages not only have a large fan base, but they also have an active community behind them.
In this article, we will look at the top programming languages of the future. So, if you want to know which programming language to use to boost your professional value, stick with us until the end!
Top Programming Languages of the Future
Python
When it comes to the best programming languages, Python takes the top spot in all its glory. Python is extremely popular among developers and Data Science experts due to its ease of use and versatility.
The Python is a beginner-friendly language with an easy learning curve and syntax similar to English. Python also has excellent library support for a wide range of coding needs. Python libraries such as Django and Flask, for example, are ideal for web development, whereas TensorFlow, Keras, and SciPy are ideal for Data Science applications. Learn more about why Python is so popular among developers.
Python can create web and desktop applications, GUI-based desktop applications, machine learning models, network servers, and much more. Python’s extensive ecosystem of libraries, modules, and frameworks makes application development extremely simple. It serves as the foundation for many industry titans such as Facebook, Twitter, Pinterest, SurveyMonkey, etc.
R
R is a dynamic, array-based, multi-paradigm programming language that was first released in 1993. It supports all major operating systems, including macOS, Linux, and Windows. R is unique in that it serves as both a statistical computing environment and a graphics environment. The R environment collects software tools for data manipulation, statistical computation, and graphical display. Learn more about R career opportunities.
The Learning Programming Languages Important For The Future? R is extremely extensible and provides a plethora of statistical (linear/non-linear modeling, time-series analysis, regression, classification, clustering, and so on) and graphical methods. The R is a multi-paradigm programming language that supports object-oriented, imperative, functional, and procedural paradigms.
R, like Python, comes with an impressive set of libraries such as gplot, tidyr, leaflet, and so on. R’s scalability and statistics, and data visualization capabilities make it a favorite among developers and data scientists.
Java
When it comes to server-side application development, Java is the unrivaled organizational king. It is a class-based, object-oriented programming language used to create software, mobile applications, web applications, games, web servers, and application servers. Java has long been the most popular programming language for creating Android apps. Java is now very popular among Big Data Engineers who use it to build Big Data ecosystems.
JSTAT, Deeplearning4j, JavaML, Weka, ADAMS, Mahout, and RapidMiner are excellent Java libraries for ML development. Java is used in the tech stacks of well-known companies such as Uber, Airbnb, Google, Netflix, Amazon, and Spotify.
C#
C# is a general, flexible, and open-source, object-oriented programming (OOP) language developed by Microsoft. It is primarily used for backend development, game development, web/desktop application development, and mobile app development for Windows phones. It is based on the.NET framework.
C# is widely used due to its ease of use and well-designed architecture. It has a dedicated.NET Core machine learning platform – ML.NET – to meet the needs of Machine Learning developers. There’s also Accord.NET and ML-Agents, which allow.NET developers to create one-of-a-kind machine learning applications.
C++
C++ is a general-purpose, cross-platform programming language developed as an extension of C by Bjarne Stroustrup. As a result, C++ combines OOP, imperative, and generic programming features. It provides developers with extensive control over memory and system resources. C++’s core features of speed and efficiency enable developers to design and build high-performance applications.
C++ is a programming language used to create operating systems, embedded systems, and graphical user interfaces (GUIs). C++ is a general-purpose, cross-platform programming language developed as an extension of C by Bjarne Stroustrup. As a result, C++ combines OOP, imperative, and generic programming features. It provides developers with extensive control over memory and system resources. C++’s core features of speed and efficiency enable developers to design and build high-performance applications. C++ is a programming language used to create operating systems, embedded systems, and graphical user interfaces (GUIs).
Kotlin
Kotlin is a general-purpose programming language that is statically typed. Its design is fully compatible with Java. Kotlin compiles to JavaScript or native code because its primary target is the JVM. The seamless interoperability of Kotlin and Java allows for much faster and more efficient Android application development. As a result, Kotlin has a promising future in Android development.
Kotlin has a simple structure and can be used for web development, desktop app development, and server-side development in addition to Android development. Kotlin is a concise, safe, and tool-friendly programming language (you can bundle it with any Java IDE or even build via the command line).
JavaScript
JavaScript is a multi-paradigm, high-level web scripting language. It is compatible with object-oriented, imperative, and declarative programming styles. Text, dates, regular expressions, and standard data structures are all supported by JavaScript’s application programming interfaces (APIs). It is one of the three core technologies that power the World Wide Web (along with HTML and CSS).
Although JavaScript and Java share naming conventions, syntax, and standard libraries, they are fundamentally different. As mentioned by book writing team It works well with Java and is very simple to implement due to its HTML integration. TensorFlow.js, Brain.js, machinelearn.js, ConvNetJS, Mind, Synaptic, and Neuro.js are some of the libraries available for developing ML models in JavaScript.
Conclusion
Now that you know which programming languages are in high demand in the job market, you can expand your skillset to include at least one (preferably multiple!) of these high-paying programming languages.
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