Incorporation of AI with Data Science

Data Science and Artificial Intelligence are two different but closely related domains. Data science is only a subset of AI. The use of data science extends beyond the realms of free VM hosting. The use of AI, today, is not confined to forecasting weather. In a very short time, AI has emerged as the broadest turf in technology.

In fact, so broad that mathematics, programming and communication are now a part of Artificial Intelligence. The birth of AI merged some of the most crucial fields that once existed independently.

Data science and AI are two most confusing spheres of technology. Only a handful of people, or more appropriately experts, have the technical know-how of how closely AI works with Data Science. To make referring to the duo, we shall, henceforth, adopt Data Science and AI as our abbreviations for Artificial Intelligence and data science respectively.

Things that you probably do not know about data science

Noticed how google ad comes up with the right recommendation every time you browse? Or maybe, how YouTube’s home screen is flooded with videos from your favourite sport?

To optimize web experience apps send a huge volume of data as you browse the World Wide Web. Almost simultaneously- as you are sending data- you also receive optimized data, which is intended solely for you.

Data science is more popular than you think. There is barely a place where data science is not used.

But why AI with data Science?

To answer the above question we must first know how AI works, why AI works, what is it that AI works with?

Answering the last question first, because it is the easiest.


AI works with pretty much everything. It works with your smartphone, your computer, your Amazon Alexa, and even with your car: provided you own a Tesla.

We will work our way backwards from the last to the first question. “Why AI works?” is the next in the queue. Because it simplifies doing things. Humans, despite being the smartest living being, are prone to committing errors. No matter how small be the possibility of mistake, there is always some possibility nonetheless. In controlled tasks, computers are faster, accurate and cheaper.

How AI works is the subject matter for this article. To spill beans on the same, AI and DS work closely. So closely that without data science AI cannot be imagined.

How AI works with data science?

Data science uses scientific and mathematical techniques to obtain useful insights from structured and unstructured data.

Where does all this data required to implement data science come from?


Remember the amazon’s reference above. Sites store data on what you view, and purchase, and in turn, customize web pages to display ads for those products.

Explaining Data Science/Artificial Intelligence

What oils the wheels of data science jams its engines. The data in a DS doesn’t come in the way that algorithms are made to work on. A freshly acquired data is clustered, unsorted and is full of irrelevant, useless information. Unstructured data is nothing but unreadable. Data Science arranges, sort, structure, and filter data and in the process makes it comprehendible for AI algorithms.

The sole purpose of data science is to make data as comprehensive as possible.

Now, what AI has to do with DS then?

AI systems are the ones that fetch this data at first place and work on the DS-structured data to produce useful results at the user’s end. AI systems, to visualize, are analogous to cash counters: collecting and lending cash to customers. The only difference being that AI collects and lends data instead of cash.

How intelligent are AI systems?

AI systems, at present, are nowhere as intelligent as humans are. But, we cannot undermine the fact that AI has made considerable advancement over the past few years. DS has proved to be the backbone for AI. Without DS, unstructured data would remain so, let alone the chances of working and obtaining useful insights.

AI tries to mimic the way humans work. To tackle unseen situations, it makes use of data collected in the past to learn new things. Much like humans do. In order to be able to learn new things from experience, one needs to have experience.

Humans have a brain, and the last time I checked, my computer had no brain of its own. To continue learning on its own, AI needs data piled up from the past. More importantly, the data must be


for AI algorithms to work upon and to be able to implement actions. Took the hint from bold-italics? DS helps artificial intelligence figure out solutions to real-time problems by linking similar data obtained in the past.

Take, for example:

You were born and brought up in a city where people play soccer. In fact, it was a city where people only played soccer. And so you learnt soccer, too. You recently moved to a new city that plays only hockey. One of your friends in the city invites you for a hockey match, and once you are there, hands you a hockey-stick.

What now? All your life you only played soccer.

This is where human intellect guides us based on our experience and by perceiving things that are new to us.

Not surprisingly, you put up a great show in the hockey match, although you never played hockey even once in your life.


Data Science pulls off similar things for AI as does intellect for humans. It allows AI to find appropriate meaning from huge pools of data collected over time.

Thus, without Data Science AI will reduce to merely a collection system with piles of unorganized data, with no technical know-how of how to work on it.

We hope the above article helps you obtain a clear understanding of Artificial Intelligence and Data Science. To make things simple and easy to comprehend, texts are supported with relatable real-life examples. Comment on the box below to help us know things we do not know. In case, you want us to write about something, do not forget to mention the same.

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