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What Are the Programming Languages Required for Data Science?

If you ask me to describe the current IT market for new developers, it is competition. With the increasing popularity of IT jobs, you can expect the competition to get intensified. So, if you are a programmer and looking to build your career in this field, you left with no option other than upgrading your skill. If you are looking to become a great programmer, you need to select the Best online data science masters, and you need to learn the below programming languages. 


Java is one of the most used open-source programming languages used for many years. When it comes to big data, many tools such as Spark, Hadoop, Hive, and Flink are written in Java. It comes with a significant number of libraries and tools to develop your coding techniques. The application of Java is widespread, and many big enterprises look for developers with Java expertise. There are many courses available to complete your Masters in data science online training in the current market. 


Python comes with a bundle of advantages, and because of this reason, it has a special place in programming languages. It is an open-source, object-oriented, and flexible language; it is easy to learn. The programming language offers the most vital advantage of the ease of coding; Python’s programming syntax is similar to English. As a result, you no need to focus on the language; instead, you can focus on the logic. Python data science is the must-have weapon if you want to upgrade your skills.


When it comes to relational database management systems, you just can’t ignore the SQL or Structured Query Language. Since a data scientist’s role is to convert the raw data into useful insights for making decisions, SQL plays an essential role in the data retrieval process. To grow your career as a data scientist, it must know how to extract data from the various databases and play with it. 


MATLAB is the best choice to handle the data files such as images, videos, sensors, binaries, telemetry, and other real-time formats. It is available with a full set of machine learning and statistics. Additionally, it includes advanced methods like system identification, nonlinear optimization, and plenty of prebuilt algorithms to process videos and images, control system design, and financial modeling. 


It is an extension of the popular language Java and also called a scalable language. It is compatible with JVM or Java Virtual Machine, and it is the primary tool when it comes to dealing with a massive amount of Big Data. It’s a must-have tool for the data scientists since it supports both higher-order functions and anonymous functions. 


R is the unique programming language, and it brings several unique features that are not present in any other language. So, it is necessary to learn R if you want to advance as a data scientist. It is a vector language, and it can do many tasks at a given point in time. The functions available in R can be used to a single vector without including it in a loop. R’s uses are gradually becoming famous, and hence it is essential to learn this if you want to get a Professional Certificate in Data Science.

C (C++)

C++ has a permanent place in any data scientist arsenal. The learning of C++ is essential, as well as more accessible. It is simple to use and one of the fastest programming languages in the IT industry. Since it is a low-level language, it offers data scientists to have broader command over the applications. 


When it comes to data visualization, JavaScript is the champion among the other tools. The data visualization task becomes more straightforward with the vast library JS comes with. The Tensorflow.js release, JS, can bring machine learning into the play and allow the developers to reap the benefits from it. 


It is another open-source programming language, and it is effortless to access. It is intuitive and comes with high efficiency since this exceeds the speed of Python and R. Hence it is a must to have weapons for the data scientist in their arsenal. 

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