Programming languages form the cornerstone of technology industries. People are using computers and the internet more and more every day for tasks they cannot complete manually; programming languages help make this possible. With rapid advances occurring constantly in this industry, keeping up can be hard; in this article we discuss five programming languages you should study by 2023 in order to remain ahead of the game.
2023 is expected to see unprecedented technological industry expansion, driven by advances in AI, machine learning, and big data technologies that drive innovation and open up opportunities for software developers. Therefore it's crucial that software developers stay abreast of emerging programming languages which will become highly in demand in 2023.
Python
Python is an interpreted programming language widely used for machine learning, artificial intelligence and web application development.
One of the primary draws to Python's success is its intuitive design and ease of use, making it ideal for novice programmers and newcomers. Furthermore, Python features built-in features designed specifically to be intuitive for beginner programmers as well as more experienced coders alike.
Python provides developers with an expansive library of modules they can leverage quickly when building complex applications, with some of the most popular libraries including:
- Pandas
- NumPy
- Matplotlib
- Scikit-learn
- TensorFlow
Key Features
- Object-Oriented Programming (OOP) support
- Easy to learn and use
- Open-source and free
- Large standard library
- Dynamically typed
- Interpreted language
- Cross-platform language
- High-level language
- GUI programming support
- High-level data structures
R
R is a programming language and environment designed for statistical computing and graphics, widely utilized within the data science community for data analysis, visualization and modeling purposes. R boasts an expansive library of packages which make it ideal for creating statistical applications; its growing demand has quickly made R one of the industry's go-to languages.
Data science and analysis using R can be performed using several packages available. Some of the more well-known ones include:
- Rcpp [Seamless R and C++ Integration]
- R6 [Allows the creation of classes with reference semantics]
- tibble [Provides a ‘tbl_df’ class (the ‘tibble’) that provides stricter checking and better formatting than the traditional data frame]
- rlang [A toolbox for working with base types, core R features like the condition system, and core ‘Tidyverse’ features like tidy evaluation]
- ggplot2 [Data visualization]
- dplyr [Data manipulation]
- tidyr [Data cleaning]
Key Features
- Open-source and free
- Cross-platform language
- Large standard library
- Object-Oriented Programming (OOP) support
- High-level language
- Data analysis and visualization support
- Machine learning support
- Community-driven development
- Interoperability with other programming languages
Lisp
Lisp has been around since 1958 and is known for its unique syntax and ability to handle complex tasks efficiently. Lisp is often employed when developing artificial intelligence applications and it has become the language of choice among AI researchers - making Lisp an excellent language to learn if your interests lie in AI or machine learning.
Key Features
- Interactive environment
- Code as data
- Macros
- Garbage collection
- Dynamic typing
- Functional programming support
- Symbolic reasoning support
- Extensibility
Java
Java is a general-purpose programming language widely used for developing enterprise, mobile and web applications. Java has been around for over 25 years and offers an ecosystem of tools and libraries which make it a fantastic option when it comes to developing large scale apps. As the Internet of Things becomes an even greater force in society, the demand for Java will likely only continue to increase by 2023.
There are many AI libraries available in Java that can be used for various purposes. Here are some of the most popular ones:
- Apache Jena
- d3web
- Tweety
- Neuroph
- Stanford CoreNLP
- Java Machine Learning Library (Java-ML)
- Weka
- Jenetics
- Spring Roo
Key Features
- Object-Oriented Programming (OOP) support
- Platform independence
- Automatic memory management
- Large standard library
- Security
- Multithreading support
- Exception handling support
- High performance
C++
C++ is an impressive programming language widely utilized for the creation of high-performance applications like video games, operating systems and computer graphics. As an object-oriented language with an intensive learning curve and flexible memory allocation mechanisms for developers, it promises great control over memory allocation and system resources - which may remain appealing features in 2023 when demand for such high performance apps continues to increase.
There are various AI libraries available in C++ that can be used for various purposes, but here are some of the more popular ones:
- Flashlight
- OpenNN
- DyNet
- Shogun
Key Features
- Object-Oriented Programming (OOP) support
- Low-level memory manipulation
- High performance
- Large standard library
- Platform independence
- Exception handling support
- Operator overloading support
- Multiple inheritance support
Conclusion
These are the top five programming languages you should learn in 2023 to stay ahead of the competition. Python, R, Lisp, Java and C++ all offer unique advantages that may help keep you on the cutting-edge. From artificial intelligence and data science applications to high-performance applications - there's sure to be one or more languages out there which meet your specific requirements.
FAQs
Q1. What programming language should I learn first?
A. If you are new to programming, we recommend starting with Python. Python is a beginner-friendly language that is easy to learn and has a vast library of modules that you can use to build applications quickly.
Q2. What are the benefits of learning a programming language?
A. Learning a programming language has many benefits. It can help you develop problem-solving skills, increase your creativity, and improve your logical thinking abilities. Additionally, programming is a highly in-demand skill, and it can lead to many career opportunities in the technology industry.
Q3. Is it necessary to learn multiple programming languages?
A. It's not necessary to learn multiple programming languages, but it can be helpful. Different languages are better suited for different tasks, and learning multiple languages can broaden your skill set and make you more versatile as a developer.
Q4. How long does it take to learn a programming language?
A. The amount of time it takes to learn a programming language depends on several factors, such as your prior experience, your learning style, and the complexity of the language. Some people can learn a language in a few weeks, while others may take several months or even years to master a language.
Q5. Are there any free resources available for learning programming languages?
A. Yes, there are many free resources available for learning programming languages. Online courses, tutorials, and forums can all be excellent sources of information and guidance. Additionally, many programming languages have open-source communities that provide free resources and support to developers.
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