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Top 10 programming languages for data science

Top 10 programming languages for data science

Top 10 programming languages for data science:

“Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge from data across a broad range of application domains.”

Data science is a growing field at present. If you are a computer science student then you have very big career opportunities in this field. If you are considering starting a data science career, the sooner you start coding, the better. To choose the right programming language for data science that will help you become a data scientist, first, we must look at what data scientists do in their daily work.

A data scientist is a technical expert who uses mathematical and statistical techniques to manipulate, analyze and extract information from a huge amount of data. Data science can also be known as machine learning, deep learning, network analysis, data mining, etc.

There are a hundred programming languages which are used in data science for diverse purposes. But some programming languages suited data science very well; they provide high productivity and performance to process a large amount of data.

The data science certification course in Indore is one of the best courses which provides many languages and technologies for students to learn data science. They provide the best programming language which suits data science. In this article, we will look at 10 top data science programming languages.

  1. Python
  2. R
  3. SQL
  4. JAVA
  5. Scala
  6. C/C++
  7. JAVA Script
  8. Matlab
  9. Julia
  10. SAS

Python: 

Python is an open-source, general-purpose programming language. It has broad applicability not only in the data science industry but also in other domains like software development, web development, and video games. Python has a broad library that can be modified by the programmers according to their needs because we know that data science is working on a huge amount of data and handling this data is very complex. It can perform all kinds of operations, from data preprocessing, visualization, deep learning models, analysis, and statistical data. Python is one of the most powerful languages for data science. 

If you want to be a Python expert then the data science institute in Delhi is here to help you. There are hundreds of students enrolling in this course.

R: 

R is an open-source, domain-specific language, explicitly designed for data science. It is very popular in finance and academics. R is not as popular as python for data science but it is perfect for data manipulation (insertion, deletion), processing, machine learning (it is a domain in which we teach a machine to decide by their experience), visualization, and statistical computing. 

Whether you are new to a data science course or you are an expert in it R is the perfect choice for data science. 

SQL:

 SQL stands for the structured query language. In data science, we analyze huge data and get valuable information from it but we have to store this data. SQL is a language that helps to store data in the database. It is a domain-specific language that allows manipulation to programmers in a database system they can edit and extract data from the database. SQL is one of the common languages if you learn data science. Knowing about SQL structure allow you to work with many other database systems like SQLite, and MySQL.

JAVA: 

Java is an open-source object-oriented programming language. It works with real-life entities. It is a very robust and powerful language. For data science security is just because we are using a large amount of data and losing information is a common issue that’s why JAVA is also the good language that suits data science. Data science is a domain that works on big data, big data is the technology that stores a huge amount of data in a database system which very difficult task for any traditional database system, and big data is based on java language. In big data we use Hadoop technology for storing and analyzing data and Hadoop is based on the JAVA language.

SCALA:

Scala has become the best programming language for machine learning and big data. It is widely uses in big data, in big data Scala is used for processing the data which is stored in the database system. it is not a very common language that is known by everyone and also it is not top ranking language but if you ever heard about big data then you should know that Scala has a big scope in data science. 

Scala is a multi-paradigmatic language explicitly designed to be a clearer and less wordy alternative to java. Java code is very complex and difficult to understand that’s why scala is used in big data for reducing the complexity of programming language.

C/C++:

If you are a computer science student then you heard about the c and also the c++ language because c is the beginning language for every student. It can be very useful when it comes to addressing computationally intensive data science jobs. C and C++ are faster than any other programming language and in data science, faster analysis is very important. Due to their low-level nature c and c++ are among the most complicated language to learn. Mastering in c and c++ is a smart move that can make a great difference to your resume and give a different kind of impact in interviews.

JavaScript:

According to the stack overflow developer survey, 2021 javascript is a top preferred programming language. JavaScript is a client-side scripting language, versatile language. It is used with HTML and CSS for creating interactive web pages. Java script is mostly used for web development in the front. JavaScript supports popular libraries for machine learning and deep learning. It is very popular among web developers.

Matlab:

 Matlab is a language mainly designed for numerical computing. It provides a powerful tool to carry out mathematical and statistical operations and it is also a great analyzer programming language for data science.

SAS: 

SAS stands for the statistical analytical system. It is a software environment designe for business intelligence and numerical computing. It is widely use in major forms in many sectors, big markets, etc. 

Julie: 

Julie can be considering a data science rising star. It is already use in the world as a numerical computing programming language. Julie has a highly effective tool compared to other programming languages. It still has a small community. It does not have many libraries such as Python and R. 

Above is some top language which is popular in data science and data science training course in Delhi is the best institute that helps you to become certified data scientists.

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