Data Science is a broad field which deals with study and analysis of data. In the current age of internet and information technology, petabytes of new data is getting created on a daily basis. Many companies then dig into this statistics to look for logical patterns and use these correlations to make predictions about the market and customer behavior. Data Science courses does not depend on any one computer language or software. A statistics scientist will basically use any programming language or data visualization tool which can help them understand the data they are dealing with.
Java on the other hand is a programming language. It can be used to create applications and has tremendous potential. Java is one of the most popular programming languages in software industry and there is almost no cap to the quality and variety of software tools that can be created using this programming language.
The background needed to become a Data Scientist
The most popular programming languages presently in the Data science domain are R and Python. However, as mentioned earlier, fact science is more about the ability to understand and analyze data than what tool you use to do so. Apart from the need to know basic computer programming, data scientists also need to be conversant with statistics and logical reasoning.
Being simple and readable does not mean that it will take time to execute. No, it's not like that. In fact, Python programming language is one of the faster and attractive language Data Scientists have ever used. If we compare it with some popular programming languages, we will see that it takes only one third the volume of Java code and one fifth the volume of C++ code to perform the same task. The way common expressions are used make Python codes look attractive as a whole. Another thing that Data Scientists love about this language is that it takes almost minimal time to execute instructions.
Scope of a Java programmer
Java is definitely one of the most robust programming languages being used extensively in the software industry. Applications of Java can be found in almost every aspect of computer use, from website development to finance and accounting. Java is fundamental and if you are a good Java programmer, you can easily hone your skills and fine tune it for statistics science. There are some tools like Big Data and Hadoop, which are used extensively by data scientists that are based on Java.
The demand for data scientists is only going to increase in the coming few decades. At the same time, Java is not going to go out of fashion anytime soon. Java is fundamental to development. Data science course is fundamental to application. While there are many Java programmers all over the globe, given its history in software engineering, and the wide range of applications for which Java is already being used as a backbone, being a Java specialist doesn't necessarily mean that you will have a good job. It is crucial that you develop your skills specifically for a particular application, in this case for the analysis and visualization of facts.
Even though lot of robust tools already exists for data analytics certification, one has to remember that the amount of statistics being produced today is increasing with every passing day. This means, as time passes, new tools will be needed which can handle more and more facts in tangible time framework. It will not matter if these tools are based on Python or Java.