Top 5 Programming Languages for Data Science

Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from both structured and unstructured data. Data Science is related to big data and data mining. Data Science involves unifying statistics, data analysis, machine learning and their related methods to understand and analyze actual phenomena with data.

In 21st century, Data Science has gained much popularity. Data Scientists are in much demand by companies these days. To be a good data scientist, you need to learn top programming languages that are essential for Data Science. Below are few programming languages that are important to learn if one wants to become a data scientist:

  1. Python:

It is a high level programming language that is based on interpreter. Python has a vast array of libraries that makes it a preferred language to learn for data science. It is a very easy language to learn. Python has scientific libraries like Pandas, Numpy, Matplotlib, SciPy, scikit-learn, etc. One should know about these scientific libraries to solve complex Python problems.

  1. R:

R language is used especially for statistically oriented tasks. Statisticians learn this language for statistical analysis. One can learn and use R language for data analytics and statistics but there is a drawback also of this language. R is not a general purpose programming language. So, it is not used for tasks other than statistical programming. Some of the features of R are:

  • It is an interpreted language.
  • It can handle complex linear algebra. Therefore it is used in neural networks.
  • Using RStudio, it is easier to connect to database. There is a built-in package called “RMySQL”. This package provides connectivity of R with MySQL.
  1. SQL:

SQL is Structured Query language that is used to retrieve or modify data in the database. It is very important for Data Scientist to know how to retrieve data from Database. SQL has different implementations like MySQL, SQLite, PostgreSQL, etc. SQL is highly readable language and one should learn it to master Data Science.

  1. Scala:

It is a general purpose programming language that has features of both object oriented technology and functional programming language. Scala is an ideal language to deal with large volumes of data. Scala facilitate parallel processing on a large scale. Since Scala is not easy to learn, therefore it is not for the beginners. Scala is used along with Spark to deal with large volumes of data.

  1. Julia:

It is a simple programming language that is used for scientific computing. Julia is used at places where complex mathematical operations are required. Julia is an ideal language to solve complex mathematical problems at very high speed. Julia is widely recommended as a language for Artificial Language.

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