Hi everyone welcome back to another youtube video in today's video we're going to talk about
what are the first things you need to learn if you want to become a data scientist
data scientist has been a term that has been thrown around in the industry specifically in
the tech field in the recent years especially after the harvard uh harvard study called it
the sexiest job in the 21st century uh which is debatable and definitely a topic for another video
but you can see that it has gotten so much attention because of that and also there are
obviously like some good signs to be good sides to being a data scientist so because of that there's
a lot of information on the internet some is good some is okay and some is just does not make sense
at all so i am going to share some of the things that have personally helped me transition and what
i have learned from my experience for those of you who don't know i come from a non-tech background
and i became a self-doubt data scientist i went to business school then transitioned to becoming
working as a data engineer and then became a self.data scientist um if you have not watched
in my previous video where i talk about my journey i'm linking it here so make sure to
give this video a watch and see you might find it useful so before we jump into the video make
sure to give this video a thumbs up to help with the youtube algorithm and subscribe to my channel
if you would like to hear more from me on the topics of data science as well as career related
uh topics so talking about uh what is the first thing you need to learn well let's step back a
bit so in terms of becoming a data scientist first thing i would suggest to figure out data science
is an umbrella term and the term data scientist is used very liberally that it means it does not mean
the same thing to one person versus what it means to the other person and the same stands for the
companies that are hiding for data scientists in some companies data scientists by data scientists
they mean applied scientists a person who is a developer times data scientist in some companies
a business analyst is considered a data scientist so um keeping that in mind what i would suggest
you to do is first figure out where exactly i'm going to link this video here where i show that
diagram in terms of what exactly you need to do look at that diagram figure out where exactly do
you want to be on that diagram do you want to be in the middle which is kind of more of like like
a generalist data scientist then there is more technical which goes into applied scientists then
there's a machine learning side and then there's more at the bottom there's more data analyst focus
or business analyst focus so first thing you need to do is figure out where exactly do you want
to be on that venn diagram and once you figure that out i promise you your your your path your
your journey is going to be much simpler because if you don't know where you want to be on that
diagram you're going to be all over the place you're going to be learning statistic you're
going to be learning machine learning you're going to be learning python you're going to be learning
tons of other things believe me the data science field is huge and you can easily get lost
learning trying to learn everything so if you're able to narrow down your focus able to narrow down
what you want to be and then work backward it's it's only going to help you so let's say you have
figured that out um and you want to uh you want to be a generalist you want to be a journalist data
scientist which is basically somebody who has good business knowledge has a good statistics knowledge
good machine learning knowledge and understanding of software development
process and is able to combine as well as product management and is able to combine
all these together and apply their knowledge to solve business problems so you have three options
one is you can go back to school you can enroll yourself in a data science degree program
and you can follow through that program that curriculum and then graduate with a degree and
build some projects and then look for a job the other option is the second option is you can
do that through a bootcamp bootcamp is a version it is a it is a i'd like to think about it
in a way that is the degree program but um it teaches you everything that a degree
program teaches you but in a much condensed fashion um and that's why those programs are
some normally like eight to twelve weeks and those are intense time periods because you uh intense
programs because you have to learn a lot during that short time period so boot camp is another
is another option that it requires a lot of your attention so for a degree program you might be
able to do it if you're already working um so you might be able to do that part-time finish that
degree program for a boot camp i feel like you need it needs your it needs your like dedicated
attention to be able to get the full advantage of the program so um those are the two options the
third option is which is something that i did and a lot of people do end up doing is going the self
teaching route and that is through learning um through like bunch of courses learning on your own
uh from peer mentoring from doing the work and all of that everything combined watching
youtube videos um and i am primarily going to be focusing on that last bucket today in terms
of the self learning and for those of you who are trying to do that what are what is the first thing
you actually need to get good at to be able to get get your journey started um so for me personally
what was super super helpful and i would highly encourage you to consider that is uh starting with
and i know a lot of people start with python like there's an advice out there that says let's start
with python some advice says that you go and do r some say is like go learn sql i think those
are absolutely okay but those are that's okay advice but let's step back a bit sql python r
is a tool to apply data science it's not the data science by itself so if you really want to learn
the knowledge learn the field i would suggest you to start with statistics for those of you who are
already working as data scientists you would agree to this that the statistics is the fundamentals of
any data science rules whether we're talking about a data scientist generalist or we're
talking about a machine learning scientist or we're talking about applied scientists
so statistics are the fundamentals of any data science role so the first thing i would suggest
you to do is start with statistics and once you have figured that out then you can add more to it
whether that is python or whether that is going more deeper into machine learning a skill set but
like starts with the basics start with statistics and when it comes to learning um learning into how
do you learn that there are multiple ways to learn if you have taken statistics as part of your uh
schoolwork like i think that's pretty much enough there is not much to statistics it's just the
basic fundamentals and it doesn't change much so whether you learned it from your curriculum from
your course that you have taken at school or you learn from a book or you watch a youtube video and
like combine all those concepts together i think anywhere you can learn statistics can be learned
anywhere because the concepts do not change the concepts the statistics concepts do not change
the teaching style changes from where you're learning from so i get i guess like it all comes
down to like your learning style how you learn best whether that is through video content whether
that is to reading or whether that is through taking a course so figure out what what works
for you and then start with statistics build that foundation and once you have built that foundation
then you can go to the next step um and we can talk about it in the next video but then you can
start um learning the coding languages and there's a i have a lot more to say on the
coding languages uh which one to get started at and it's a slightly controversial topic because
different people have different opinions on what language to learn um i definitely have my one of
my own so i will definitely share that in another video but um in terms of learning statistics
yes definitely start there for me what was helpful is um i started learning statistics
one of the books that my manager recommended me at that time when i was working as a data engineer
is let me show you so this was and i promised this is not sponsored sponsored i just found it in my
cupboard um and i was like this is perfect for this video because um this is something that i
did use when i was learning uh statistics so this is a book practical statistics for data scientists
uh by peter bruce and andrew bros so you are welcome to buy it from anywhere you want
and learn statistics that way um and then in addition to that you can watch youtube videos
there's a lot of ton of youtube videos um on statistics that and khan academy is a great
resource for those of you who haven't taken i haven't i'd be surprised if you haven't
pursue ever if you haven't taken a video on khan academy but it's a great resource for
uh and it does a great job simplifying complicated topics so what i normally did
is i got this book i did not read everything um i would start like initially with a concept
then i would read about it in this book i would read a blog about it and then i'll watch youtube
videos or khan academy videos which simplify the topic for me further because i feel like learning
it just like reading through it one time it's a little bit harder i just i just want to see like
how different people would explain it differently so that's what i would normally do is like like i
would read it here and then i would go watch a youtube video and i learned a topic for another
video again i know i keep saying that financial literacy i became financial literate last year
and that exactly was my route i would read it in the book then if i needed to build further on
that topic i would go to youtube or i would read a blog and things like that to further my knowledge
so hopefully this was useful i know there's a lot of information out there in terms of how
to get started this is personally in this is my opinion that in in my opinion and in my experience
you need to start with statistics um and then you can add on top of it because statistics is
the foundation of data science so hopefully this was helpful for you if you have any questions feel
free to leave it in the comment or if you have any feedback for me or ideas for future videos
feel free to let me know alright i'll talk to you in the next video have a good one bye