Programming

Currently, Python is doing to Java what Java did to C/C+ when Java was at its peak. Back in those days many applications which needed performance did still use C/C+ but accompanied by high maintenance costs from the sheer amount of code written to achieve simple tasks and also the difficulty in building OS and machine independent applications. However, things changed in favor of Java when computers became powerful and hardware costs came down. People (like me) who looked down on using Java to build applications started accepting Java's advantages in building applications. Back then Python was primarily used as a scripting tool and was used in building test automation (and it still is being used for that purpose too.). Now comes the glorious age of data science and various tech startups in e-commerce and social space. What could be done by writing a thousand lines Java code is achieved in a couple of lines of code in Python. This means that there is less maintenance of code. On top of this, Python does not have arcane syntax and the code is pretty much human readable. For machine learning applications there are very good libraries such as Pandas, sci-kit-learn, etc. The primary advantage with Python is that focus can be put on solving business problems rather than spending the most time on fixing bugs related to faulty code. Coming to web development frameworks such as Django, Tornado provides a wide range of needs from quick development to high-performance websites.

Hello,
In the IT world, there is an excessive demand of those programmers who are expert in the field of R programming. There is no specific eligibility criteria or any prerequisite to learn R programming at all. This is the easiest computer language. If you are smart enough, then you can even learn this language while just reading books and watching the tutorials on YouTube.
This programming is in demand, because R language can handle the enormous amount of business data. It is much possible that system may get out of order, because of storage incapacity. R programming can easily solve this problem, because this language can handle the petabytes of business data. Another big feature or advantage of learning this is that it is stastical application more than just a language. Hence, it supports embedding compiled code in other language like FORTRAN or C.
So, this makes the R Programming an essential elements for all the programmers to learn.

Hello,
Itis an extensive usable tool for industrial expansion measurement. This tool is not just used by the computer science or Information Technology expert, but with the advancement of Technology, this tool is now useful for Mechanical engineers as well. Hence, its utility is increasing day by day. MATLAB (MATrix LABoratory) is a tool for numerical computation and visualization. The basic data element is a matrix, so if you need a program that manipulates array-based data, it is generally fast to write and run in MATLAB, unless you have very large arrays or lots of computations, in which case you are better off using C. You need to be graduate in the field of Computer Science or Information Technology stream, in order to learn the functions and operations of MATLAB. But apart from that, PGDS -Post graduate Diploma in Statics is most important Professional degree that are demanded by the companies for MATLAB coding expert job. Salary prospective is dynamic. It depends upon your qualification, company and etc. On the average, the average salary of MATLAB expert is between Rs. 4 lacs pa to Rs. 5 lacs pa.

Hello,
In the IT world, there is an excessive demand of those programmers who are expert in the field of R programming. There is no specific eligibility criteria or any prerequisite to learn R programming at all. This is the easiest computer language. If you are smart enough, then you can even learn this language while just reading books and watching the tutorials on YouTube.
This programming is in high demand, because R language can handle the enormous amount of business data. It is very much possible that system may get out of order, because of storage incapacity. R programming can easily solve this problem, because this language can handle the petabytes of business data. Another big feature or advantage of learning this is its stastical application is more than just a language. Hence, it supports embedding compiled code in other language like FORTRAN or C.
So, this makes the R Programming an essential elements for all the programmers to learn.

Firstly, I'd be cautious to make a claim that C++ is better than Java. There are pros and cons to both sides.
C++ is basically more power to the programmer (since one can break past all sorts of abstractions), and runs natively instead of on a virtual environment (and hence is also platform dependent). A C++ application can manage its own memory in more finer ways than a Java app can. In C++, one can overload operators, access physical addresses and override values there. One can throw and catch any type (.) and do some nasty stuff around all that. On the other hand, in Java, one can sit back and basically just deal with OO abstractions and code them up in one-way, regardless of the underlying platform. Fine-grained memory management is harder. One can play around with GC params for optimizations and get really far this way, but anything more is not really achievable. In C++, you can easily get as deep as you want to.
But, also remember, with great power comes great responsibility. An irresponsible Java developer would be less harmful to your software, than an irresponsible C++ developer would be. In that sense, Java is a relatively easier and simpler language to work with, than C++ is. With C++, a lot of responsibility and burden is on the shoulders of the programmer and with Java, a lot of this, is taken care of, by the system.
There is also a popular performance myth with C++ and Java. Since C++ runs natively, it used to run faster in most platforms than Java does, given the VM is basically emulated. However, this is increasingly being rendered moot, as JVMs end up being very powerful, and processor speeds and architectures have evolved a lot over time.