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
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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
