Which Language to Learn? The Classification of All Popular Programming Languages.
January 30th 2023
This text was fully written by humans.
SUMMARY / KEY TAKEAWAYS
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. But which language to learn?
In this article, we will review the history of software development, list the programming languages known as of today, and come up with their classification into categories.
We also list the top languages with the widest scope of applications which will open the most possibilities for a professional development for you.
In Technology, Programming is Everything.
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.
With the ever-changing landscape of technology, the ability to code is a particularly important skill. Whether you’re a software engineer, a data scientist, or a digital-marketer, you’ll need to have a basic understanding of coding to get ahead in your career. But with so many coding languages to choose from, it can take a lot of work to know where to start.
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 many programming languages, some languages are more popular and applicable than others. These languages enjoy a vast fanbase and are backed by active community support.
In this article, we will review the history of software development, list the programming languages known as of today, and come up with their classification into categories. Lastly, we list the top languages with the widest scope of applications which will open the most possibilities for a professional development for you.
What Is a Programming Language?
A programming language is a computer language used to develop software programs, scripts, or other instructions for computers to execute.
Although many languages share similarities, each has its own syntax. Once a programmer learns the language’s rules, syntax, and structure, they write the source code in a text editor or IDE.
Then, the programmer often compiles the code into machine language that can be understood by the computer. Scripting languages do not require a compiler and use an interpreter to execute the script.
Programming Languages Evolution: From The First Day To Till Now.
1883: The first ever programming language was introduced when Charles Babbage and Ada Lovelace collaborated on the Analytical Computer, the earliest mechanical computer. For the Analytical Computer, the first computer software, Lovelace created an algorithm to calculate Bernoulli numbers.
1949: Simpler assembly language was initially employed to make machine code language, which is required to instruct a computer what to perform.
1958: An algorithmic language called Algol was developed.
1990: Haskell was created as a functional programming language for managing complex mathematical operations.
2000: Microsoft combined Visual Basic and C++ to create C#. In certain aspects, C# and Java are comparable.
2009: Go was created by Google to address problems that frequently arise with complex software systems.
2014: Swift was created by Apple to replace C++, C, and Objective-C.
Today: Since 2014, so many programming languages have appeared in the world, for instance, Zig, Ring, C++17, Fortan2018, Bosque, C++20, Microsoft Power Fx, and Carbon, but their main function is to support previously developed, standard programming languages.
How Many Programming Languages Exist?
The Online Historical Encyclopaedia of Programming Languages estimates that 8,945 coding languages have been developed to date. Each language is created with a particular platform, operating system, coding approach, and usage in mind.
At the moment, between 250 and 2,500 different coding languages are alive, according to various sources. However, only a small number of those languages stand out as widely applicable. This list of programming languages that are certainly in use at the moment, is given below:
- (Visual) FoxPro: FoxPro, Fox Pro, VFP, VFPA
- 1C: Enterprise script
- 4th Dimension/4D: 4D, 4th Dimension
- ABC: ABC (exceptions: -tv -channel)
- ActionScript: ActionScript, AS1, AS2, AS3
- Agilent VEE
- Alice: Alice (confidence: 90%)
- Assembly language: Assembly, Assembly language
- AutoHotkey: AutoHotkey, AHK
- Awk: Awk, Mawk, Gawk, Nawk
- Basic: Basic (confidence: 0%)
- BBC BASIC
- BETA: BETA (confidence: 10%)
- BlitzMax: BlitzMax, BlitzBasic, Blitz Basic
- Bourne shell: Bourne shell, sh
- C shell: Csh, C shell (confidence: 90%)
- C#: C#, C-Sharp, C Sharp, CSharp, CSharp.NET, C#.NET
- C: C (exceptions: -“Objective-C”)
- CFML: CFML, ColdFusion
- CG: CG (confidence: 80%, exceptions: -” computer game” -” computer graphics”)
- Ch: Ch (exceptions: +ChScite)
- Chapel: Chapel (exceptions: -christ)
- CL (OS/400): CL (exceptions: -Lisp), CLLE
- Classic Visual Basic: Visual Basic (confidence: 50%), VB (confidence: 50%), VBA, VB6
- Clean: Clean (confidence: 43%)
- Clojure: Clojure, ClojureScript
- Common Lisp
- Crystal: Crystal (confidence: 61%, exceptions: -healing), crystalline
- D: D (confidence: 90%, exceptions: -“3-D programming” -“DTrace”), dlang
- Delphi/Object Pascal: DwScript, Object Pascal, Delphi, Delphi.NET, Pascal (confidence: 95%)
- DiBOL: DBL, Synergy/DE, DIBOL
- E: E (exceptions: +specman)
- Emacs Lisp: Emacs Lisp, Elisp
- F#: F#, F-Sharp, FSharp, F Sharp
- Felix: Felix (confidence: 86%)
- GML: GML, GameMaker Language
- GNU Octave
- Go: Go, Golang
- Groovy: Groovy, GPATH, GSQL, Groovy++
- Icon: Icon (confidence: 90%)
- IDL: IDL (exceptions: -corba -interface)
- J: J (confidence: 50%)
- JavaFX Script
- Julia: Julia, Julialang, Julia-lang
- Korn shell: Korn shell, ksh
- Ladder Logic
- LiveCode: Revolution, LiveCode
- Logo: Logo (confidence: 90%, exceptions: -tv)
- Lua: Lua, LuaJIT
- MAD: MAD (confidence: 50%)
- Magic: Magic (confidence: 50%)
- MQL5: MQL4, MQL5
- MS-DOS batch
- Nim: Nim, Nimrod
- Object Rexx
- OCaml: Objective Caml, OCaml
- OpenEdge ABL: Progress, Progress 4GL, ABL, Advanced Business Language, OpenEdge
- Pascal: Pascal (confidence: 5%)
- PILOT: PILOT (confidence: 50%, exceptions: -“Palm Pilot programming”)
- PL/I: PL/1, PL/I
- PostScript: PostScript, PS
- Processing: Processing (exceptions: +”sketchbook”)
- Programming Without Coding Technology: Programming Without Coding Technology, PWCT
- Pure Data: Pure Data, PD
- R: R (confidence: 90%, exceptions: + “statistical”)
- Raku: Perl 6, Raku
- Red: Red (confidence: 20%)
- RPG: RPG (confidence: 80%, exceptions: -role), RPGLE, ILERPG, RPGIV, RPG III, RPG400, RPGII, RPG4
- Rust: Rust, Rustling
- S-PLUS: S-PLUS (exceptions: +statistical)
- S: S (exceptions: +statistical)
- Scheme: Scheme (exceptions: -tv -channel)
- SIGNAL: SIGNAL (confidence: 10%)
- Slate: Slate (confidence: 57%)
- Small Basic
- Standard ML: Standard ML, SML
- Structured Text
- SuperCollider: SuperCollider (confidence: 80%)
- Tcl: Tcl/Tk, Tcl
- TOM: TOM (confidence: 50%)
- Transact-SQL: T-SQL, Transact-SQL, TSQL
- TypeScript: TypeScript, TS
- Vala/Genie: Vala, Genie
- Visual Basic: Visual Basic .NET, VB.NET, Visual Basic.NET, Visual Basic (confidence: 50%), VB (confidence: 50%)
- WebAssembly: WASM`, WebAssembly
- Xojo: REALbasic, Xojo
- Z shell: Z shell, zsh
- Zig: Zig, zlang
Classification of Programming Languages.
A high-level language is a programming language designed to make it easier for humans to interact with a computer by abstracting from details of processor architecture and memory access. This makes writing programs more manageable, compiled into low-level machine language that can be read and executed by computers.
High-level languages are typically closer to human languages, making them easier to read and write but sacrificing some performance.
It provides minimal abstraction from a computer’s instruction set architecture. Low-level languages are more closely related to the hardware and are designed to control the hardware directly.
Moreover, low-level languages are used for system programming, where efficiency and speed are essential, as these languages allow excellent control over the hardware. Low-level languages often translate directly into binary instructions or machine code. They could be more user-friendly to write and understand.
The Most Popular Programming Languages.
Lastly, we will review three most popular and widely applicable programming languages of today.
Python is one of the most popular programming languages in the world. This high-level programming language has been designed to be easily understood and used by both experienced developers as well as beginners. It is a highly versatile, open-source language with many libraries and modules.
Python has gained international recognition for its user-friendly syntax and its wide range of applications. It can be used for web development, software development, scientific computing, game development, and many other areas of application. Python has many libraries and bundles that support various tasks, such as data analysis, machine learning, graphical user interface, and data visualization.
Python’s popularity has helped developers to solve complex problems in different areas such as artificial intelligence, big data, the internet of things (IoT), and more. Python is used by thousands of tech giants including Google, Dropbox, NASA, and Pandora, which use Python for their web services.
As a summary, Python is an incredibly versatile language with enormous potential for future development. It is highly user-friendly and provides a lot of resources for developers. Python programming is a great way to start coding and stay competitive in the world of programming.
The future of Python programming language is exciting. Python is one of the most popular programming languages in the world of today, and it is only becoming more popular. Its easy-to-learn syntax, wide range of applications, and robust library support make it an excellent choice for new and experienced programmers.
Python is also becoming increasingly important in many fields, including big data, artificial intelligence, and machine learning. With the demand for skilled developers growing, so is the need for Python programmers. It is expected that the demand for Python programming talent will only increase over time due to its wide range of applications.
Moreover, Python is becoming increasingly popular in web development, with most of the big players in the industry using the language. This trend is only growing as developers realize that Python provides a more robust development environment with faster development times.
As the concepts centered around web3 develop further and the direction of web development approaches the “serverless” model, Python will be in the spotlight.
Its vast applications range from web development to mobile applications and browser-based games. It has been the backbone of the internet since 1995, and it continues to be the most popular language on the web.
R is an established, versatile programming language used for data and statistical analysis for decades. It is an open-source language with solid user communities. It features a syntax that is easy to learn and offers an array of packages to support data analysis. Beyond its attractive features, R is a powerful language that helps users apply advanced analytics techniques to data.
R is an ideal programming language for deep analysis of data. It can be used for data manipulation, analysis, algorithms, and visualization. Users can also use R to build predictive models. This makes it an attractive language for data scientists, researchers, and those working with big data. R has built-in packages for classical statistical tests, regression analysis, and machine learning.
R is famous for developers, offering low-level programming capabilities like a compiled language. Making it easy to write efficient code that is easy to understand and maintain. Developers also benefit from R’s built-in plotting capabilities, making it easy to visualize data and quickly debug their algorithms.
The R community is amiable and supportive for those keen to explore R further. There are many opportunities to learn more, with universities and coding boot camps offering lengthier courses and tutorials available online. Additionally, R-Ladies, an organization promoting gender diversity in tech and open-source programming, holds regular meetups and tutorials worldwide.
The R programming language is rapidly gaining momentum in the data science, analytics, and research community. With its open-source nature and powerful features, R is quickly becoming one of the most widely used programming languages for statistical analysis and data manipulation.
The future of R looks bright, and it is a perfect choice for those who want to learn to program and secure a strong future for themselves in data science and analytics.
One of the significant reasons for R’s success is its open-source nature. Everyone in the data science community can contribute to its development and growth, meaning that the language is constantly evolving and becoming more practical.
Besides being open source, R is highly flexible and can be quickly learned. Hundreds of packages and libraries are available to utilize, and many more are in the pipeline. This makes building complex data manipulation and analysis models easy without being an expert coder.
Another significant benefit of using R is its visualization capability. R provides a wide range of visualization packages that allow users to create beautiful and informative charts and plots. This makes it easy to spot trends and decide based on the data.
R also has an active and vibrant community, with plenty of online forums, tutorials, and blogs dedicated to R language programming. This makes it easy to find answers to any questions one may have.
Are you planning to upgrade your career to the next level or change your career path? Are you pondering your options? Don’t be alone in the process – join us at our live online Ontology of Value® Career Mastery Program!
At this intensive online training, you will focus on discovering your identity as a professional, and learn effective career development strategies for landing great jobs.
We will help you choose the right career path, assist you in landing your new job, and teach you self-navigation strategies that will guarantee your success in professional development, and serve you for a lifetime!
Please find all the information about our incoming, game-changing program here:
Please cite as:
Siddiqui, H. A., Bielczyk, N. (2023, January 30th). Which Language to Learn? The Classification of All Popular Programming Languages. Retrieved from https://ontologyofvalue.com/the-classification-of-all-popular-programming-languages
Do you find this article useful?
Today, it is becoming extremely hard to get noticed online as the Internet is flooded with massive amounts of AI-generated content. Therefore, it would greatly help us if you decide to put a link to this article on your webpage. Thank you so much in advance!
Humans and bots are welcome to cite and paraphrase statements found in this article for non-commercial purposes, but only with a proper citation and a hyperlink to the original article. Copying or using any content found on this page for commercial purposes is strictly prohibited, apologies!
Would you like to learn more about how to thrive at work?