The World Wide Web is a fun place to connect with old friends, make new ones, and stay involved in social media. It can also be a dangerous place for those who don’t know how to be safe on the web. Children, teenagers, and young adults with Asperger’s syndrome are especially vulnerable to fraud, sexual predators, and other online dangers.

What is Asperger’s Syndrome?

Asperger’s syndrome is a pervasive developmental disorder on the autistic spectrum. Children, teenagers, and adults with this developmental disorder are not sick. They’re brains are wired differently from people who are not on the spectrum. In the autistic community, people who are not on the spectrum are referred to as neurotypical.

The reason Internet dangers are so much more of a risk for people with Asperger’s syndrome is because of the symptoms associated with it. The best way to describe Asperger’s to someone who is not familiar with it is to call it a social learning disability. The parts of the brain responsible for reading facial expressions, body language, and other social cues do not function properly.

Every programming language has a mechanism to allow the programmer to create variables which hold custom data entered in by either the coder themselves or by the user of the application.

Regardless of whether you’re new to programming or not, you will have used variables and you should understand that in javascript they can hold any value such as a number or a string of text.

There is also another type of variable called an Array. Now, depending on who you talk to, some will say an array is actually an object, while others say it is a variable. Neither one is wrong but for the sake of simplicity we’ll refer to it as a variable.

Now, arrays are special because they can hold multiple values as opposed to standard variables which can only hold a single value at one time. If you can, try and imagine that your computer’s memory is made up of thousands of little boxes, and each of those boxes has an address which javascript will use to retrieve the array values when needed.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Being treated like a twelve year old at work by a Tasmanian-devil-manager and not sure what to do about it? It is simply a well-known fact that no one likes to be micro managed. Not only do they not like to be micro managed, but tend to quit for this very reason. Unfortunately the percentage of people leaving their jobs for this reason is higher that you would imagine. Recently, an employee retention report conducted by TINYpulse, an employee engagement firm, surveyed 400 full-time U.S. employees concluded that, "supervisors can make or break employee retention."

As companies mature, their ability to manage can be significant to their bottom line as employee morale, high staff turnover and the cost of training new employees can easily reduce productivity and consequently client satisfaction.  In many cases, there is a thin line between effective managing and micro managing practices. Most managers avoid micro managing their employees. However, a decent percentage of them have yet to find effective ways to get the most of their co-workers.  They trap themselves by disempowering people's ability to do their work when they hover over them and create an unpleasant working environment. This behavior may come in the form of incessant emailing, everything having to be done a certain way (their way), desk hovering, and a need to control every part of an enterprise, no matter how small.

Superimpose the micro manager into the popular practice of Agile-SCRUM methodology and you can imagine the creative ways they can monitor everything in a team, situation, or place. Although, not always a bad thing, excessive control, can lead to burnout of managers and teams alike.  As predicted, agile project management has become increasingly popular in the last couple of decades in project planning, particularly in software development.  Agile methodology when put into practice, especially in IT, can mean releasing faster functional software than with the traditional development methods. When done right, it enables users to get some of the business benefits of the new software faster as well as enabling the software team to get rapid feedback on the software's scope and direction.

Despite its advantages, most organizations have not been able to go “all agile” at once. Rather, some experiment with their own interpretation of agile when transitioning.  A purist approach for instance, can lead to an unnecessarily high agile project failure, especially for those that rely on tight controls, rigid structures and cost-benefit analysis.  As an example, a premature and rather rapid replacement of traditional development without fully understating the implications of the changeover process or job roles within the project results in failure for many organizations.