hey everyone welcome to the session by intellipaat 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 and see where it stands well before we begin with the
session make sure to subscribe to the Intellipaat's YouTube channel and hit that
Bell icon so that you never miss an update from us here is the agenda for
today we'll begin by taking a quick introduction to data science followed by
which we can check out where data science is actually used and after this
we can check out what artificial intelligences and some facts about
artificial intelligence at the same time and after this we're gonna compare data
science head-on with artificial intelligence and guys if you have any
queries make sure to head down to the comment section below I do let us know
and we'll be happy to help out of the earliest and guess if you're interested
in doing an end to end Course certification in data science
Intellipaat provides the data science architect master's program where you can
learn all of these concepts thoroughly and earn a certificate at the same time
well without further ado let's begin the class coming to the first item on
the agenda it is introduction to artificial intelligence I am sure in the
past decade and in fact in this decade we've been hearing a lot about
artificial intelligence right so what is artificial intelligence it is very
simple guys it is a theory and the development of computer systems to
basically mimic human intelligence or we can even stay at it as you know machine
performing a task which would actually require some sort of human intervention
there well there are many tasks where artificial intelligence at this point of
time is actually a lot better than human beings for example our we have image
recognition we have speech recognition process of decision making and
translations when you think about all four of these basically you will know
that there is some sort of human intervention required because we are
trained to look at images we understand speech and our brain is logical enough
to you know perform very good decision making and decision taking steps but
then when we talk about translations as well pretty much we have been trained to
understand different languages where we can you
know translate between one to the other as well but nowadays all this can be
done faster more efficiently and eventually better than human beings by
making use of machines guys so where are we with artificial intelligence
today when artificial intelligence has been so subtly integrated into our lives
we don't even notice it is there anymore guys why do we see this stick with me
for the next couple of slides and you will understand just this because when
you look around you there as artificial intelligence everywhere and also you
might have heard of the term such as artificial intelligence is the best
career path of this decade and what not and that is a heavy statement because we
are just at the start of this decade but then all the trends and all the
analytics which have been performed all the surveys which have been conducted
pretty much says that artificial intelligence as a career path and the
technology is on the rise and it will be trending for the next ten years and as
you can see artificial intelligence has the biggest community ever well if
something is trending and if something is constantly on the number one spot for
the last couple of years and definitely it attracts the attention of everyone
right so that's basically that and then guys coming to where artificial
intelligence has been used in this world well this is why I told you it has been
very subtly integrated into our lives everything from Google assistant Cortana
you know there's Siri there's big speeders Alexa and much more so you can
talk to your phones you can talk to your computers you can talk to your machines
to get so much done in fact there are smart homes being implemented for the
last couple of years well all you have to do is ask Alexa to do stuff for you
you know Alexa can unlock the door for you Alexa can turn on your TV home
theaters and you know pretty much turn on the lights move away the
curtains and pretty much everything so when you think about it it has been
there around us for a while now but then when we talk about the actual trending
stuff about artificial intelligence you know when we talk about revenues
especially for the next five years you can see from the graph all the way from
2016 to 2025 the amount given is in million dollars so you know pretty much
it was three fifty seven million dollars in 2016 basically the revenue
generated by enterprise applications from 357 it has been predicted that in
2025 it's gonna hit thirty one thousand two hundred and thirty six million u.s.
dollars guys so imagine the growth as you can see on your screen I am sure you
guys can figure out that it is an exponential growth
just a quick info in case you guys are looking for end-to-end course
certification in data science Intellipaat provides the data science
architect master's program where you can learn all of these concepts thoroughly
and earn a certificate in the same the link is given in the description box so
make sure to check it out and without further ado let's get back to the class
and then when we talk about how much research is going on with respect to
artificial intelligence here is the thing in the year 2000 there was less
than around one thousand one thousand technical papers which are actually
published but then when you talk about 2015 and up there is skyrocket and from
in fact from 15 all the way till 25 the numbers just keep going as high up as
you can think as so we started all the way from 1500 in 2015 it hit somewhere
around 18,000 and now you know pretty much it is very more than 40,000 papers
which have been published guys so it is that nine times growing every single
year is what we can tell and then coming to this slide where we're trying to see
where artificial intelligence fits in well there are a couple of steps when we
talk about data you know steps such as data generation data storage data
processing and inside so the first steps pretty much include data generation and
data storage and this gets covered all together by the world of big data guys
and then coming to data processing and actionable insights
well artificial intelligence here we go because when we talk about data
processing we can make use of machine learning deep learning neural networks
and there are many other concepts guys natural language processing you know
support vector machines and much more - pretty much process all of the data and
at the end of it we have very good data analysis and analytics tools which make
use of artificial intelligence to give us beautiful visualizations which can be
used to derive actionable insight and then finally coming to the comparison
between data science and artificial intelligence on the first point we'll be
discussing is the meaning well guys did as you can see is a very detailed
process which basically involves and you know pre-processing the data
performing some analysis on this data at the end of the analysis comes 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 but then coming to artificial intelligence artificial
intelligence is basically 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 while coming to point number two it's the skills well when you talk
about data science again or 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 guys well when we talk about artificial
intelligence it has got a lot to do with algorithm design algorithm development
efficiency conversions and in fact even deployment of all of these design and
developed products guys but then coming to the next point it is the technique
here is where there is a lot of difference between artificial
intelligence and data science in data science you know we are actually majorly
concerned about making use of data analysis and data analytics guys so data
analysis where we'll be using pass data to analyze the present tense in a very
simple term and with respect to 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 but 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 it can be a lot of concepts as deep learning neural networks and much
more as I just mentioned in the couple of slides ago
well basically coming to the next point it is the knowledge well when we talk
about data science data science was actually established you know to find
hidden patterns and hidden trends in data to make more sense of the data and
to make it a more friendlier entity but then we talked about artificial
intelligence you need to know that you know with respect to artificial
intelligence it 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
guys then coming to the next point quickly is processing with respect to
processing 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 but then 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 of 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 being there is right so
coming to the next one is the goal of these technologies well with respect to
data science complex models you know are basically built by making use of various
insights various facts about the data it's a lot of statistical techniques
modeling and whatnot but then we talk about artificial intelligence well
artificial intelligence was meant to build models that emulate cognition guys
but emulate cognition what we basically mean as it again we're trying to make
the machines self sustained enough so that where it would not require certain
human dependencies and 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 and then coming to the salary of the develop words well the
average salary of a data scientist is around hundred and thirty thousand US
dollars per year 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 of time
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 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 so to summarize the
differences between these two basically I want to say that artificial
intelligence you know makes use of these loops of perspection 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 coming to when we should go about using data science or
artificial intelligence 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 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 as well guys well to keep it to the scope of all the
viewers of this particular video we had to simplify it to present it here guys
now coming to the companies which make use of data science and artificial
intelligence well we have everyone from Apple Google Amazon Twitter of Facebook
Nvidia and thousands of other companies who make use of data science on a daily
basis 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 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 and results
just a quick info in case you guys are looking for end-to-end course
certification in data science Intellipaat provides the data science
architect master's program where you can learn all of these concepts thoroughly
and earn a certificate in the same the link is given in the description box so
make sure to check it out I hope this session was very informative
for you all if you have any more points you wanna add on this data science
versus artificial intelligence video or if you have any queries in general make
sure to head down to the comments section and do let us know we'll be
happy to help out at the earliest and on that note have a nice day