Choosing data science as a career is something every youth is looking upon these days. The demand for data scientists in every industry is growing substantially. In today’s highly competitive world, the data science aspirants are left with no solution but to upskill themselves as per the emerging needs. Without mastering the trending ones, your skillset remains incomplete. The knowledge and application of programming languages signify the data science industry.

What is a programming language?

A programming language is a formal language consisting of a set of instructions that produce various outputs. These languages are used in computer programs to implement algorithms and have multiple applications. There are several programming languages for data science as well. Having prior knowledge of more than one language skills give you versatility and competence as a data scientist.

Data scientists should learn and master these languages as it is an essential tool to realize various data science functions. Therefore, we have assembled the list of top 5 data science programming languages that aspirants need to learn to improve their careers.

Why choose these programming languages?

There are more than 250 programming languages in the world today. Data scientists have a large selection of technologies for implementing a wide variety of tasks. Both the efficiency and the cost of the development project will depend on the chosen programming language. You can check out the right programming language for your project by following the mentioned tips.

Top 5 Data science programming languages

1. Python

Python holds a special place among all other programming languages. It is the most used data science programming language in the world today. According to reports, at least for the next five years, Python proficiency will top the required skill set in data science. It is commonly referred to as the easiest programming language to read and to learn.  Python is best for data science because of its capacity for statistical analysis, data modeling, and easy readability.  Another reason for this success of Python in Data Science is its extensive library support for data science and analytics. There are many Python libraries that contain a host of functions, tools, and methods to manage and analyze data.

2. R

When talking about Data Science, it is impossible not to talk about R. R is a high-level programming language built by statisticians. It is a very unique language and has some really interesting features which aren’t present in other languages. R is not just a language but a whole environment for statistical calculations. It allows you to perform operations on data processing, mathematical modeling, and work with graphics as well.

3. SQL

SQL (Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system. Having SQL skills can be the biggest asset for machine learning and data science professionals, as SQL is the most preferred skill set for all the organizations.  Knowledge of SQL tables and queries can help data scientists while dealing with database management systems.

4. Java

Java is one of the oldest programming languages and it is pretty important in data science as well.  It has a great number of libraries and tools for Machine Learning and Data Science. Some of them being, Weka, Java-ML, MLlib, and Deeplearning4j, to solve most of your ML or data science problems. Also, Java 9 brings in the much-missed REPL, that facilitates iterative development.

5. JavaScript

Data scientists should have knowledge of JavaScript as it excels at data visualization. There are a lot of packages for statistical analysis and machine learning. TensorFlow is able to help with the creation of web-based AI projects with simplified functions. This versatile language is capable of handling multiple tasks at once. It is one of those data science languages that can be quickly and easily scaled up for large applications.

Now that you know the top programming languages for data science, it’s time for you to practice them and master data science as a career. When you have planned to attain, get it from the experts. Check out for more details on various courses on Data Science.