This is the fourth element of the Big Bang of Data Science, that is Code AI from the Start to The End.  

I don’t want to stick to that _abstract and direct_ definition from the academic book, on the meaning of coding, but from the industrial one. So, I believe **CODING** is a language syntax that machines use to communicate to or with. In other words, just like humans, machines use their own language, recently in the form of a digital form of [0, 1], to speak to each other or with us. So, if you code something it’s as if you are authoring a text, where the code is the structure and syntax of that language you author of, and the rules and structure of that language must be then obeyed. As if a text is authored using a human language, the form of outcome must be a book, or a paper, or similar forms; if you code using any programming language, then the outcome form is going to be a GUI form which can be of taking input as arguments and outcome results to screen, or just a script that execute certain tasks.  

So, since we have established that level of understanding on the meaning of coding, then let us connect the dots with the aim of [The Big Bang of Data Science]. In the main introduction of it, I have mentioned that the outcome from the first two books: [Research from the start to the end] and [analysis from the start to the end] you have an analytical model which is used as an input to the third book __prediction from the start to the end__ the outcome was a __predictive model__.

Then I set the argument that we shall use this model in somehow; that was two possible ways: (a) as a backend GUI interface, e.g. _desktop app, mobile app, or desktop app_. Alternatively, (b) we can use the model to embed it into a machine_ that machine then act as smart one so to speak.

In the first edition of [the Big Bang of Data Science] I have established the fact to transform this predictive model as a backend to a __GUI__ interface. That is exactly the main aim of this material. Where we shall discuss how to fix this __predictive model__ as a backend for an __interface__ . We are going to use a specific form in this edition that __GUI__ or interface shall be __desktop application__. However, this idea can span to other forms such as __mobile app__, or __web app__, but the concept is the same.

We are going to use a common programming language in this material, that is __Python__, however alternative options are possible as well. In addition, we shall utilize most of the __CURD__ operations that standard operation apps would do, moreover, the utilization of __Database__ structure, even though, the choice would be primitive, however it can span to more complicated scenarios. As you will most likely understand that Python is the language we write, so to transform that script into a GUI we can utilize available packages such as PyQt to accomplish that aim. Finally, two projects will be built, the first is to solve a classification problem in health domain, and the second, to watch a real-time price change from a finance domain.