Ultimate Guide to Programming Languages 2024

Computer programming powers all the websites and apps we rely on for work, entertainment, and social communication. Even if you don’t work in tech, programming can make you a more valuable asset at work. State governments have some of the highest levels of employment for computer programmers, while the highest-paying industries for programmers include finance and oil and gas companies, according to the Bureau of Labor Statistics (BLS).

Even if you’re a hobbyist, programming skills may come in handy as the internet continues to further shape society. Ready to boost your career with this in-demand skill? Here’s a breakdown of the most popular programming languages.

Different types of programming languages are designed to accomplish different tasks. Some, like Python, are high-level and are closer to human language, while low-level languages, like C, are similar to how computers “think.” We can break up thousands of programming languages that exist today into six main types that are not mutually exclusive.

Want to learn code? With anywhere from 250-2,500 coding languages in use today, it makes sense to start with some of the most commonly used and popular languages.

You’ll find that many of these languages are similar or commonly used together. Some were created to extend the capabilities of others. Some are so flexible they could be a part of almost any IT project. Below are the 12 most popular programming languages to learn.

Python is a high-level, interpreted, object-oriented language that can also be used as a scripting language to connect components. Python can be used for SEO and data analytics. It also has important cybersecurity uses and can analyze malware, scan ports, and send and receive packets. It’s the most popular programming language of 2022 and is considered one of the easiest languages to learn.

JS is widely used for front-end development; most websites use this coding language to make interactive features. With JS, you can display updates, interactive maps, and animated graphics. It can also be used to create browser and third-party APIs.

TypeScript, a superset of JS, is an open-sourced programming language that allows users to easily identify types of data as well as errors.

Java is an object-oriented, compiled programming language designed specifically for coding apps and services for the internet. It looks and feels like C++ but is simpler to use.

It is the second most popular programming language to learn and is also considered to be difficult to hack. You can start to build a portfolio as a novice by completing some beginner projects like making your own currency converter or calculator.

SQL is used for managing relational database management systems such as MySQL, PostgreSQL, and SQLite. You can use SQL to store and alter information in a database as well as optimize database performance. One strength of this programming language is its ability to integrate with other languages like Java. It also uses English-like statements, making it easier to understand.

C# is an object-oriented language that runs on the .NET framework. It can be used to develop dynamic web pages, games, and workflow apps. It provides operators that can perform arithmetic, compare operands, use Boolean logic, and perform other tasks.

Plenty of paid and free online bootcamps are available to learn C#.

Go is an open-source programming language developed by Google. It is modeled after C and was inspired by Python’s simplicity. Go is a favorite choice for cloud-based or server-side applications and is also used for artificial intelligence, data science, and robotics. Go is popular for its simplicity and efficiency, and was intended to replace server-side languages like Java and C++.

C is a versatile, general-use coding language first developed in 1972 at AT&T Labs. C++ is a superset of C. You can use C++ for both procedural and object-oriented programming. On the other hand, C is strictly a procedural language. The syntax for C and C++ is similar to those of Java and Python. C is considered faster but more difficult to learn than these two popular counterparts.

Swift was first released only for native iOS development in 2014 and remains one of the top languages for iOS app developers. It was created with the intention of simplifying Objective-C, another top choice for Apple developers. Swift runs up to 2.6 times faster than Objective-C.

Swift is one of the easier coding languages to learn. A 2016 update made Swift compatible with the Linux operating system, and in 2020, it became available for the Windows operating system.

PHP is used to create customizable and dynamic websites. It supports object-oriented and scripting programming paradigms and works closely with HTML. A PHP interpreter connects the user with the web server, databases, and the responses sent back to the user.

Back-end and full-stack engineers choose this language for its ease of use. It also has data encryption and access restrictions, bringing in built-in cybersecurity. You’ll often see online forms use PHP.

Ruby is an object-oriented scripting language. It’s a general-purpose language that is often used for web applications, data processing, and automation tools. Thanks to its straightforward syntax, Ruby is easier to pick up. The language is different from Ruby on Rails, which is a web development framework that extends the Ruby language.

Kotlin is an object-oriented language that works and exchanges information well with the Java virtual machine (JVM). It’s often used in combination with Java and is the preferred language of Android, though you can also use it for web development and data visualization. Java files can also be converted into Kotlin files.

So which programming language should you learn? It depends. Every language has its strengths and capabilities. Whether you’re brand new to coding or you’re on your way to becoming a systems programmer, here’s what programming languages you might want to get into depending on your career goals.

Scratch is unique in that it was developed by MIT Media Lab to help teach people how to code. It’s a block-based, drag-and-drop programming language that is used educationally in schools.

JavaScript is a great way to dip your toes into building a dynamic, interactive webpage as a beginner project. Java, which is unrelated to JavaScript, is a simple, object-oriented programming language that is easier to learn and reads like English.

Python is arguably easier to learn than Java because it’s an interpreted language. This means the language executes instructions directly, unlike a compiled language, where a programmer’s code is changed to machine code by a compiler.

SQL will make it easier to navigate relational databases, which can help you produce research and write reports.

A full-stack developer fulfills the role of both a front-end and back-end developer. Some languages are more useful for front-end developers and client-side development, while others pull more weight for back-end developers and server-side development. Languages like JS, Kotlin, and Swift are useful for both areas.

Kotlin is growing in popularity for Android app development. Swift is the most popular language for iOS, but legacy apps will still use Objective-C. Java has persisted as a scalable solution for Android apps.

Go is a popular language for building scalable backend services behind mobile apps. Frameworks like Kivy and BeeWare make Python a good choice for cross-platform applications, and JS is a favorite for back-end and front-end app development.

The addition of new frameworks like NodeGUI, Proton Native, and AppJS makes it possible to use JS for desktop applications. C# can be used to develop desktop apps that run on .NET. It also has nullable types and automatic garbage collection.

Python can be used to connect components, while Java’s cross-platform capabilities make it popular for platform-independent development. Go, Kotlin, Swift, and Ruby are other popular choices. Rust is good for writing scalable applications.

If you want to be a systems programmer, C++ will likely be useful. This language is backward compatible, meaning it can interact with older versions of C. C is also considered a good language to know because its design informed the programming languages that followed.

Rust allows you to balance efficient programming with high performance and control over hardware. Java and Python are also helpful to know here.

Data scientists may want to know Python for its libraries that give access to data analytics algorithms. SQL is useful for retrieving and editing information from data sets. JavaScript is useful for visualizing data.

Among the more advanced languages, R can perform statistical operations, while Scala performs well in large organizations and can handle high-volume datasets. C++ pairs well with Python and can be used to compile large datasets.

As a software developer, you can use Python for data analysis, prototyping, and automation. Other versatile programming languages like Java and JavaScript will be useful to have in your toolkit of programming languages. PHP is useful for server-side scripting and command-line scripting.

C++ is critical if you’re interested in game development. TypeScript and SQL are also generally common and can also be useful for software developers. Swift and Kotlin are also popular.

As AI continues to reach more parts of our world, you could be a stronger candidate for tech roles by learning the top programming languages for machine learning, computer vision, generative AI, and more. Here are some of the top programming languages for AI.

Java is used in AI systems that must integrate with existing systems. Java’s libraries, stable runtimes, and cross-platform capabilities make building and deploying AI apps more accessible. Deeplearning4j, for instance, is a framework for running deep learning on the JVM.

Developers can use Java to build customizable algorithms that can more easily handle large datasets. Companies like Google, Netflix, and LinkedIn all use Java in their machine-learning models.

Python is considered to be the most popular programming language for machine learning. There’s a wide variety of AI libraries and frameworks available. The NumPy library, for example, can be used for scientific computing with Python.

Its simple syntax speeds up prototyping and allows developers to create and test AI models faster. It’s a popular option for rapid application development. If you’re starting out, you’d be best off learning Python 3, the newest version of the language.

JavaScript allows for real-time data processing and can be used for interactive web pages with live data visualization. It uses an event-driven model to update pages and take user inputs without lagging.

The brain.js neural network API integrates deep learning, while TensorFlow.js allows you to develop machine learning models in the browser or Node.js, allowing you to analyze images and speech at the front end.

Lisp uses parentheses-based syntax. It is flexible and can support multiple programming types. Its logic programming capabilities make it a top choice for AI. It interfaces with TensorFlow, allowing you to expand the language to neural networks.

In terms of AI, Lisp can be used for automated reasoning, natural language processing, and game-playing algorithms. The language is able to rewrite its own code, which makes it adaptable for automated programming applications.

C++ is preferred for its speed and efficiency for high-performance AI algorithms. You can use it to execute machine learning programs quickly without using a lot of memory, making it a good choice for AI projects that require a lot of processing power.

Game developers tend to use this language, and many games use AI. From video game companies like Blizzard to government agencies like NASA, many companies use C++ today.

A programming language designed particularly for data science, R is used for statistical computing as well as data mining. R is used by more than 2 million statisticians and data scientists around the world.

R has linear and nonlinear modeling, time series analysis, classification, and clustering. Its data visualization and manipulation are essential for AI development. However, it is more useful for early-stage research than deploying machine learning into a product.

Julia is a relatively new, easy-to-learn programming language. It’s very flexible and has several libraries for machine learning, optimization, and data visualization. It’s been adopted for data science programming. Other use cases include scientific simulations, bioinformatics, and computational biology research. Julia is designed to be as simple as Python and as fast as C.

Note: The insights on this page — excluding school descriptions — were reviewed by an independent third party compensated for their time by BestColleges. Page last reviewed June 11, 2024.