Top 10 Programming Languages for Data Science

Programming Languages for Data Science

We are already seeing; the need for data storage as we move to a digital age. We require data science understanding to manage such big data. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and other knowledge to organize unstructured data into structured.

The demand for data science is increasing day by day. So, if you want to start your career in data science, you should know the programming languages used in data science. Here, we have listed the ten best programming languages for data science.

Programming Languages for Data Science

In this section, we are going to discuss the top 10 programming languages to learn for Data Science. So, let us dive in.

1. Python

Of course, we start this list with arguably the most trending programming language in the world right now – Python. The obvious reason behind that is its flexibility. You can do web designing, develop software or web applications, and even build mobile apps with Python. However, the real reason for its immense popularity is that most experts believe it is the best language for AI and Machine Learning.

The fact that the language is open-source makes it more acceptable. Also, there are hundreds of online communities where you can seek help. As the demand for data science will likely increase in the near future, we can expect Python will dominate the market. Of course, one more reason to learn Python is as it is easy to learn.

2. R Programming

The second one in this list is a bit unconventional – R Programming. If you are really into Data Science, R can be of great help. There are several features that are available in this programming language that make it stand out from the rest. One of the core reasons people admire R is because it is a vector language. Naturally, this adept language can do multiple functions at once with ease.

However, some believe this language is exclusive to Data Science; several other reports also suggest that R is efficient enough for financial studies, genetics, and medical science. Either way, R is a unique language and has a definite edge to it. It is not that hard to learn either, and the career scopes seem vibrant.

3. SQL

Structured Query Language or just SQL is probably the most popular database management programming language in the world right now. The reason coders love this one is that it can work with other languages seamlessly. So, if you are a web designer and need to store databases, SQL is your solution. Many mobile app developers prefer SQL, as well.

The biggest advantage of learning this language is you can use it with almost every popular language for any kind of project. So, it widens your work scope and makes it ideal to learn. SQL is easy to grasp, and almost every training center has an SQL curriculum in it.

4. C (C++)

C and C++ are vintage programming languages that will never go old no matter which time we live them. It is and will always be one of the best programming languages for making enterprise solutions. A Data Scientist’s toolkit is incomplete without C, followed by C++. Granted there are alternatives available nowadays, but a large chunk of companies still prefers the language more than others.

The spectrum is enormous if you learn C, as there are multiple domains you can try depending on your preference. There are tons of training centers to date that teach C and C++. So, learning will not be going to be an issue.

There is another perspective on this as well – since many companies will face a financial crisis, they will not be going to change their core functions to an extreme level. So, if you are an expert in C++, there are still ample job opportunities for you in the future.

5. Java

It is okay to say that Java is arguably the complete programming language of all time. It has been around for more than three decades, but still, it offers something robust every day. There are hundreds of library features that you can take help with alongside thousands of frameworks.

With Java, the possibilities are endless. You can do website designing, build software or mobile apps, create desktop applications, and many more. Java has always been a fan-favorite of most business houses. That is why it is still preferred as an enterprise solution. The fact that Java is an open-source programming language, you can easily customize it to whatever you need for wrapping up a project.

6. JavaScript

JavaScript is next on our list. This one is probably the most loved front-end web designing language in the world. So, if you have a knack for building websites, this is something that you should definitely consider.

You can use a wide variety of prebuilt libraries that you can use, not to mention that JavaScript is an open-source program. So, it is super easy to customize as per project requirements. Another compelling reason for that increased popularity in recent times is the introduction of Tensorflow.js. Using this, you can do stuff related to machine learning. JavaScript is the first choice in most front-end jobs available today. So, it makes sense to learn now.

7. MATLAB

MATLAB is yet another programming language ideally suited for Machine Learning. You can also do a lot of stuff with this incredible programming language. Nonlinear optimization and System identification are the two most promising jobs that you can do. Of course, you can try hundreds of prebuilt algorithms for image and video processing, as well.

Learning MATLAB is not that hard. However, finding proper institutes may have been an issue. Of course, you can always find suitable courses online. Now, the language has a wide spectrum that is worth giving a shot at.

8. Scala

Scalable language, popularly known as Scala is one of the most competent programming languages that you should consider learning. The language is, first and foremost, an extension of Java, and it also supports JVM. With Scala, you can do Big Data programming with ease. As everyone knows, Big Data will be most likely to offer tons of job scopes; it is imperative you should be aware of Scala.

Scala is easy to learn and runs on most platforms. If you are into Data Science, you should consider learning it, as it will bolster your skills to a new degree. As it carries both higher-order functions and anonymous functions, you can pull off some incredible projects at a jet-speed time.

9. Swift

One of the simple yet powerful programming languages in this list is Swift. First of all, it is a dedicated program for building apps for iOS smartphones. We all would agree that apps are the future of technology. So, Swift will elevate your skill, and at the same time, you can be relevant to the industry’s demands.

This language is indeed fast and as promised a program for the future generation. There are some intriguing features available only in Swift that will help you to build iOS apps with minimum effort. Learning Swift is also easy, you can learn it from its official website.

10. Julia

We will wrap up this list with yet another open-source programming language – Julia. The reason for its fame is its lighting speed. Some expert studies even suggested that it is faster than R and Python. It is one of the perfect alternative languages for Python if you are interested in Data Science and AI-based projects.

You can literary explore more than 1900 packages that the language offers, and with every passing of time, more and more online communities are spawning up. Another significant reason people love Julia is it can seamlessly integrate with other languages like C, C++, MATLAB, R, Python, and many more.

Conclusion

So, these are the top programming languages to learn for Data Science that we believe you should consider learning. One thing; that you must understand, though, is there are, of course, millions of other languages that you can choose too. I hope this article was helpful to you. If you liked the article, share it with your friends. If you have some suggestions or queries, do not hesitate to leave them in the comments section below.

Posted by
Ajoy Kumar

He is a Computer Science graduate dedicated to empowering individuals to forge successful careers in programming and the dynamic world of technology and industry.

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