Data science is a vast domain that includes a number of tasks, from collecting data to transforming them into actionable insights. And at the core of these tasks lies the fundamental data science skill – the programming languages.
Currently, the demand for skilled data science professionals is soaring. Organizations are looking to maximize the power of data science and extract meaningful insights out of huge amounts of data they have gathered over time to help them with data-driven decision-making. By 2026, around 11.5 million data science jobs will be available in the US. Do you have the right data science skills and expertise to grab these opportunities?
Well, your knowledge and experience of using a variety of programming languages for data science will help you distinguish from the crowd and secure your position in highly paid data science jobs.
So, here we bring the list of top programming languages for data science mastering which will help you succeed in your data science career. Let’s start.
Python is known to be the most popular programming language in the world of data science with 66% of data scientists using it in their job. It has a huge community of practitioners and beginners helping and supporting Python users with all their problems. Moreover, its readability, simplicity, and extensive libraries further make it a popular choice among all kinds of data science professionals and developers.
R is widely known for its statistical power. To be clear, it has been designed specifically to handle large statistical computations and graphics. Users can also enjoy the flexibility and depth needed for statistical analysis with R.
It is not a general-purpose programming language like Python or R, but SQL, or Structured Query Language is an indispensable language for data scientists working with relational databases. It can easily query, manipulate, and extract data for all kinds of data-driven projects. Therefore, it is one of the go-to data science programming languages.
Though it is a newer programming language for data science, it is getting quite popular in the data science industry because of its exceptional performance and ease of use. Many data science certifications now focus on Julia's fundamentals because of its future potential.
Scala runs on Java Virtual Machine (JVM) and offers both functionality and object-oriented programming. It also has great support for concurrent and distributed programming. Thus, it is highly suitable for big data and machine learning applications.
These are some of the top programming languages in data science. Apart from these, there are some other languages that are used in data science such as:
Mastering these languages is definitely going to help you advance in your data science career rapidly.
There are several programming languages in data science, each with its own unique features, strengths, and weaknesses. Mastering all of them is quite difficult. However, you can master any one specific language that you are comfortable with and can familiarize yourself with other popular languages. This will help you perform your data science job in all kinds of situations and resources. It is also recommended to upgrade your data science skill with top data science certifications to understand how to choose the right programming language for you as well as learn their full applications effectively.
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