Demystifying The Role Of Coding In The Life Of A Data Scientist

Life Of A Data Scientist

This article is intended more for some serious myth-busting, myths which have grown around programmers, programming and its importance for a data science professional. I have met at least three very bright people who were eager to make a move into the data science universe but were constantly deterred by their lack of experience with coding. Not being able to code takes a toll on your confidence and we should do anything at all to avoid it.

Who are programmers or coders?

Coders are people who are able to communicate with a machine. They use a language which practically builds the virtual world. For instance, suppose you are playing a first person shooter on your PC and you point your mouse at a certain object and make a left click. The object on the screen bursts into flames with a piercing sound resembling that of a gunshot. This happens because a programmer has used code to make the object respond in such a manner. 

The coders are behind every virtual response be it the erasing of the previously typed word with ctrl+z to monitoring the slightest changes in climate over a long period of time.

What is their role in data science?

We use data science to find problems as well as their solutions. The primary resource that we use is data and programmers use code to manipulate the data in different ways. We need some code to perform operations like filtering out a certain name from a large list of names, as well as more complicated tasks like building neural networks with the help of the data.

It would have been impossible to move an inch in data science without the help of the coders. Data science uses filters and algorithms in order to sift through data. These algorithms need to be coded. Professionals performing data science using python is a very common thing. 53.5% of data science professionals prefer Python as their go to tool.

Is programming an essential quality in a data science professionals

If you have some coding experience under your belt, it will make your life a lot simpler in the initial stage. You will have greater freedom in terms of setting up algorithms and training machines. But that does not mean a non programmer cannot join the data science squad.

The person may have to learn coding after all at his own comfort zone. However, not knowing a language would not be a deterrent to your dream of becoming a data science professional.

Can you learn to code while working as a professional

Here is something you need to remember if you want to shine in this field. You will always have to be open to change and new knowledge. Our civilization is outrunning itself constantly so we must act like good fits and keep learning without any excuses. So, if you cannot code and you are tired of using only GUI based tools or bothering the coder for menial tasks, you go ahead and learn to code. 

What is a good starting point? 

The way the world of data science has moved so far, Python looks like a good bargain. Brands like Google, dropbox, and flipkart are pretty much standing upon Python but what is more important is its suitability for data science. Python libraries like Pytorch, NumPy, are useful platforms for preparing algorithms. It has an easy learning curve and has a lot of potential even outside the data science world. The best part is that it was not around that much when most of your peers learnt how to code hence you cannot be as far behind them as it might seem. 

How companies have used Python

Python is a general purpose language that can be used to design games as well as to train machines to learn from data. Companies run Hadoop using Python to streamline the data collection and storage. They use it to perform statistical analysis as well as to visualize data. Python is a pretty important language for the designing of neural networks.

People prefer this language simply because of its simplicity and most importantly its scalability. 

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What you take from here

Firstly you take the courage to plan a career in data science or cybersecurity engineer without having prior experience of coding. Secondly you take the confidence to start learning right now. Keep striving for excellence and at some point you will get what you wanted.