Top 10 Data Science Programming Languages for 2020

Top 10 Data Science Programming Languages for 2020

Data science is one of the emerging technologies that has led to the development of artificial intelligence, machine learning, deep learning, robotics, and IoT. Are you a professional who wants to switch your domain and work in high-paying jobs in these emerging domains? Or are you a graduate who wants to build your career path in these fields? Whether you’re a fresher or a professional, knowledge and expertise of the top Data Science programming languages will help you in your career development. Let’s take a look at the top 10 Data Science programming languages for 2020 and how they can help build your career path.

Here’s the List of Top 10 Data Science Programming Languages for 2020:

  1. Python
  2. R
  3. SQL
  4. C (C++)
  5. Java
  6. JavaScript
  8. Scala
  9. Swift
  10. Julia


Python is an object-oriented language that has the features of programming languages such as Java and C. It is used to build GUI-based desktop applications and user-friendly data structures. This open-source language is widely used in building data science, machine learning, artificial intelligence and analytics applications. It is so important that the curriculum of every Data Science course will have a section dedicated to Python coding.

  1. R

R is a vector language that has many interesting and unique features. Moreover, this language is platform independent, which means that it can be used with all operating systems. Also, it can be easily integrated with C and C++. This language is basically used for statistical analysis, data mining, data visualisation, and behaviour analysis. It is the most preferred computing language for coding government, healthcare, and enterprise mobility solutions.

  1. SQL

SQL or Standard Query Language was released in 1974 by the IBM Research Centre. This programming language is mostly used for managing databases. In Data Science,

SQL is used to retrieve or gather data from various sources. Professionals who work on data wrangling and data extraction need to be proficient in SQL.

  1. C (C++)

It is one of the oldest, fastest, and most powerful computing languages out there. This low level computing language is used to execute high level codes and operations. Based on the current market scenario, many graduates feel that learning Python or R will be enough to land good jobs. However, expertise in C (C++) coding will give a strong foundation in their coding skills. It will allow them to easily learn other programming languages and explore various domains.

  1. Java

Java is another computing language that has a rich legacy. This language is platform independent, which ensures its versatile use. It has a strong memory, high security, and high performance, all of which make it a great choice for building backend systems and mainframe data centres. Java codes are used in e-commerce websites, games, electronic applications, mobile apps, and web apps. In the field of Data Science, Java is used in building big data tools such as Hadoop, Spark, Hive, Flink, and Spark. It is also used in building Java-ML, Deeplearning4j, MLib, and other AI/ML tools.

  1. JavaScript

This object-oriented programming language is feature rich and used to build browsers and websites. It is used in both front end and back end development. This scripting language is used in technologies such as jQuery, Angular, React(JS Library), and JSON. In Data Science, JavaScript finds application in data visualisation tools.


MATLAB has machine learning and statistical functionalities. This programming language is used to create data-focussed research apps and high-end graphic user interfaces. It is used for nonlinear organisation, video processing, system identification, control system design, parallel processing and financial modelling. Also, this language is used to implement algorithms and plot data and functions.

  1. Scala

Scala is a multipurpose language that has the right blend of object-oriented concepts and functional programming. This scalable computing language is used in pattern matching and string comparisons. It is preferred in Data Science as it supports both high-order and anonymous functions. Graduates and professionals who want to build a career in Data Science will find better opportunities when they learn this language.

  1. Swift

Swift is a computing language developed by Apple in 2014. It is closest to C and has a syntax that is similar to Python. This stable language is also supported by FastAI and Google. Swift requires less coding and delivers high performance. This language is used for building iOS applications.

  • Julia

This open-source language is highly intuitive. It works at a speed that is higher than that of R and Python. The speed and versatile use make Julia one of the preferred languages for Data Science. There are more than 1900 packages in Julia with most of the libraries written in C, C++, R, Python, and MATLAB.


Good knowledge and expertise in the top programming languages will definitely open doors to numerous career opportunities. If you are interested in building a career in the field of Data Science, enrol in a certification course. Corpnce is one of the leading Data Science training institutes in Bangalore one of the the best Data Science Courses in Bangalore. The training methodology is project based to give you practical training in the Data Science tools, technologies and programming languages. Also, Corpnce offers placement support. Take the first step towards building your career in Data Science. Enrol today!