Since the past century, technology has been growing and evolving tremendously. We went from watching black and white television to having high-tech machines which detect cancer, technology has made our lives so much easier. Now with a click of a button, you can know about anything and everything. Have you ever wondered how technology has developed? The answer is data science.
Data science is a multidisciplinary field which consists of a plethora of subjects including machine learning, data structures, big data, data mining and so much more. In layman’s language, it is the science of data which helps people, especially data scientists study data and make it more intelligent. Since the study of data science also includes the study of computers, somehow, it is very necessary for a data scientist to have a good knowledge of computer programming languages. Hence, these languages play a key role in this subject.
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Some of the languages used in data science are:
- JAVA – Created in 1995, it is a general purpose computer-programming language which is class based and is one of the most independent languages known. It is mainly used in mobile applications, desktop applications and games. It is compiled by Java Virtual Machine (JVM) which converts the code to a bytecode.
- PYTHON – This language was developed before Java and it is one of the most common languages used in data science. It forms a strong base in machine language as well. It has automatic memory management and it supports many programming bases, including procedural, functional and object oriented.
- R – This language is generally used in statistics. Definition wise, it is a language used for statistical computing. R consists of a combination of areas including clustering, classification, linear and non-linear modelling etc. Technically, it provides an environment which is primarily written in C which helps in statistics for data scientists.
- It is used in storing, processing, managing and updating the data stored in databases. The language is based on algebra like relational algebra and tuple relational calculus.
- JULIA – It is a high level general purpose programming language used in complex numerical analysis and computational science. It is somewhat similar to the use of R and these languages combined help in the calculation and mathematics aspects of data science.
Besides these few languages, there are many other programming languages which are used in data science. Not only this, one is recommended to have a strong base in mathematics, statistics and machine learning in order to make the most progress in this subject. Once you start learning these languages, you will find that you understand the working of computers much more properly and can work on researching data science on your own now. So if you are interested in learning more about data science, you should definitely enroll for a course which will help you!
If you are interested in data science and want to learn more about it and the good scope it holds, then you should definitely sign up for data science training in hyderabad which will give you a strong base on the subject and also train you for the aspects it holds.
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