Artificial Intelligence vs Data Science

Artificial Intelligence vs data science. In this post, we going to see about AI vs DS with the 11 major differences and you can translate this blog to Tamil or any language using google translater. So now let’s jump into our content.

Intro :

Hey everyone welcome to the session by blogging Tamilzhan you might have heard of data science,

data science and artificial intelligence have been a really big boon to the world of information technology because this entire world is one big data problem and in this session, we’re gonna compare data science head-on with artificial intelligence.

Artificial Intelligence Vs Data science :

Then finally coming to the comparison between data science and artificial intelligence,

1. Meaning :

The first point we’ll be discussing is the meaning well guys.

Data Science :

Data science as you can see is a very detailed process that involves and you know pre-processing the data performing some analysis on this data at the end of the analysis comes to the visualizations where we’ll be generating a lot of graphs a lot of visuals and at the end of it, you gonna use all of this to perform some predictions on some future trends guys.

Artificial Intelligence :

Then coming to artificial intelligence is you know implementing a model and what this model at the end of the day does is that you know it is used to forecast certain future trends future events what might happen and how we can get there if that is the case.

2. Skills :

While coming to point number two it’s the skills well when you talk about data science again.

Data Science :

Data science you have to understand this is an umbrella term for a lot of statistical techniques a lot of design techniques and development methodologies.

Artificial Intelligence :

Guys well when we talk about artificial intelligence it has got a lot to do with algorithm design algorithm development efficiency conversions and even deployment of all of these design and developed products guys.

3. Technique :

But then coming to the next point it is the technique here is where there is a lot of difference between artificial intelligence.

Data Science :

Data science in data science you know we are majorly concerned about making use of data analysis and data analytics guys so data analysis where we’ll be using past data to analyze the present tense in a very simple term and concerning data analytics we’ll be using the past and the present data to predict the future trends guys that is why there is a small difference between analysis and analytics.

Artificial Intelligence :

Then when we talk about artificial intelligence you need to know that you know will be concerned with a lot of machine learning concepts in this particular stage it can be machine learning can be a lot of concepts like deep learning neural networks and much more as I just mentioned in a couple of slides ago.

4. Knowledge :

Well basically coming to the next point it is the knowledge well,

Data Science :

When we talk about data science data science was established you know to find hidden patterns and hidden trends in data to make more sense of the data and to make it a friendlier entity.

Artificial Intelligence :

Then we talked about artificial intelligence you need to know that know concerning artificial intelligence is to make sure whatever data we are dealing with can be autonomously handled so we are trying to remove the human from the picture when we talk about artificial intelligence to give the Machine some depth some understanding of the data to let it work on its own without the human dependency.

5. Processing :

Guys then coming to the next point quickly is processing concerning processing,

Data Science :

Again data science does not involve a very high degree of scientific processing it involves a lot of complex procedures, yes but then all of these are not the highest standards of scientific processing guys.

Artificial Intelligence :

When we talk about artificial intelligence even as the name suggests it can be a bit more complex when we talk about artificial intelligence guys because your will be having a lot of high-level processing a lot complex processing to deal with because at the end of the day we are trying to implement some sort of autonomy in the machines you know which eventually are telling the machines that they need to step up their game and to mimic the human brain and the human brain in today’s world is the most intelligent.

6. Goal :

Coming to the next one is the goal of these technologies,

Data Science :

Well concerning data science complex models you know are built by making use of various insights various facts about the data it’s a lot of statistical techniques modeling.

Artificial Intelligence :

We talk about artificial intelligence well artificial intelligence was meant to build models that emulate cognition guys but emulate cognition what we mean as it again we’re trying to make the machine’s self-sustained enough so that where it would not require certain human dependencies the next thing is that it will require some sort of human understanding to a certain level because that is what is required to achieve some sort of cognition.

7. Salary :

Then coming to the salary of the developed words,

Data Science :

Well, the average salary of a data scientist is around a hundred and thirty thousand US dollars per year.

Artificial Intelligence :

And the average salary of an artificial intelligence developer is around one hundred and twenty thousand US dollars per year guys.

This is the average amount that I’ve mentioned to keep it to the scope of all the viewers well guys what you need to understand at this point is that we have kept the average number on the screen you can pretty much have access to three to four times the salaries mentioned on your screen regardless of which country you’re working from or what company you’re working for as well guys so you have to know that these both carrier parts are very fun to work with very lucrative and at the end of the day you will have a lot of fun at your job at the same time.

8. When to use AI or DS?

So coming to when we should go about using data science or artificial intelligence,

Data Science :

Well data science is actually preferred when you need to understand and find out patterns and trends in the data it is used if you have some sort of a mathematical requirement where you need an in depth and the faster analysis of the same it is also used when you need to perform EDA EDA is basically exploratory data analysis where you’ll be hunting and pretty much going through the data to find something which might skip the naked eye as we said and then you’ll also be using it if you need some sort of improvement which is supposed to be linear which you need a constant growth in your particular concepts and also it’ll be required if you require very fast mathematical processing guys but then the last requirement is that you know there are a lot of industry requirements which will involve a lot to do with prediction for example if you’re a sales company a product company you will be concerned with what is the products you might sell next month next year the next decade or so right so predictive analytics also helps your and data science does just that.

Artificial Intelligence :

Come into artificial intelligence well artificial intelligence is a requirement if you know you require some sort of precision which is out of this world guys and I mean it when I say that because AI is made to use in full potentials in full swing when we are basically trying to get the greatest degree of precision that we can and then when we talk about decision making as well artificial intelligence is known to be faster or when we compare directly to humans in many aspects so that is that and then coming to logical decision handling again guys as humans there might be emotional interference in multiple tasks where the requirement does not call for that in that case pretty much artificial will not have any swing to any emotions and it’ll work fine and then handling repetitive tasks for humans can be a bit of a challenge but then when we talk about AI pretty much it can handle it with ease guys again working 24/7 365 days without any breaks or performing very good risk analysis risk-taking abilities and making sure you’re efficient through all of these points that I mentioned on a screen AI does it better than humans at this point of time and then there are many other points with respect to data science and artificial intelligence.

9. Companies using Data Science :

Now coming to the companies which make use of data science and artificial intelligence well we have everyone from Apple Google Amazon Twitter Facebook Nvidia and thousands of other companies who make use of data science daily.

10. Companies using Artificial Intelligence :

Then coming to the companies which make use of artificial intelligence we have everyone from Walmart labs Microsoft Genpact Accenture Ericsson KPMG and all the fortune 500 companies that you can ever think of guys.

Conclusion :

So to summarize the differences between these two I want to say that artificial intelligence you know makes use of these loops of perspective that we call and then pretty much we use some sort of planning to become intelligent in how we handle data guys but then when you talk about data science data science is all about using patterns all about using trends and pretty much you know getting at a decision faster more efficient which might have crossed the eye when we talk about data.

So in today’s world where we live data as an unruly and entity already know that but worry not concepts such as data science and artificial intelligence are in full swing to make data to make all of these processes a friendlier entity and to help us work with it faster more efficiently and with better outcomes.

Originally published at https://bloggingtamilzhanda.blogspot.com.