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It is hard to believe that the toy language built to create alert boxes in the browser is now the basis for many languages. Developers want to reach users, and if users are living in the browser, finding a way for your code to run in JavaScript is the fastest way to reach everyone.

It is not just JavaScript cousins like CoffeeScript and LiveScript that transpile to JavaScript. Even languages like Lisp, OCaml and Pascal can be converted to JavaScript and run in the browser. Python is popular in the browser on projects like Jupyter notebooks and even Java can be translated into JavaScript using tools like the Google Web Toolkit.

Java has strong IDEs

Eclipse, NetBeans and IntelliJ are some of the best integrated development environments. They were created by the Java community and fed over the years to create one of the most supported environments for writing code. Code completion and code generation algorithms may not write all of your software, but they can enter a significant amount. All of this really helps new developers to get the syntax right.

These IDEs were so popular that developers of other languages found a way to run their code inside them. If you become a professional Java programmer, you will almost certainly use one of them. In the meantime, if you want a simpler and more friendly Java programming experience, try BlueJ or Greenfoot. These “beginner IDEs” were designed specifically to learn Java.

Desktop Support Technician is known as one of the backbones of IT organization. They are also accountable for groundwork, installation, and maintenance of end user workstation equipment (laptops/ desktops) and additional peripherals including IP telephones.

Python has the cloud

The Python language found its first home in the Unix world, so it’s no surprise that clouds full of Linux boxes are natural places to find a lot of Python code. Some of the newer tools, like Jupyter, bundle code, data and explanation so people can share their insights with others as research articles come to life. Jupyter notebooks are not static documents, but interactive tools for exploration.

Others are building sophisticated tools around the language to improve research. PyTorch, for example, is a deep learning toolkit full of code, data and algorithms for analysis. Environments like this will dominate the future of data science.

There are also several good notebook hosts that add extra features to share data and handle large computational data intensive jobs. Google, for example, runs the Collaboratory, which will store your data and offer free access to GPUs for faster computing. Saturn Cloud delivers performance that can be 100 times faster than your desktop.

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