hello everyone Ken here back with another video for you if you're new to
my channel I'm a data scientist that makes videos about the broader field of
data science and sports analytics in this video I'll introduce you to the
main reason why many people struggle to learn the field of data science as a
special thanks for watching to the end of the video I'll also give you my best
advice for getting past this major hurdle it's been almost five years since
I began my data science journey and I can barely remember the struggles I had
when I was first getting started in the field honestly it had been some time
since I've learned something truly new and outside of my comfort zone and so
since we're in quarantine I decided to experiment with something radically
different I picked up one of these after starting to learn the Rubik's Cube a
flood of nostalgia came back to me and I remembered the early part of my data
science journey it seems so overwhelming to learn the math and the computer
science that is relevant for the field I came from a business background so
almost all of the concepts were completely new to me and I'm not alone
one of the most common comments that I get on my channel is that I don't know
where to start or can I really learn all of this when we think about learning the
field of data science as a whole it seems like an almost insurmountable task
there's so many different concepts and algorithms and and whatever there might
be that you actually have to learn this small learning endeavor of picking up a
Rubik's Cube helped me to remember this struggle and it holds the key to getting
past it when I first scrambled the Rubik's Cube I was completely paralyzed
I didn't know what to do basically anyway I turned it it seemed to get more
and more confusing my natural inclination was to go online and figure
out how to at least get it back to where I started once I found hundreds of
tutorials and different approaches to solving this cube and again I was
overwhelmed by just how much information there was out there
this is when I relived one of my first data science kind of lightbulb moments
the answer is to just start somewhere and it usually
doesn't matter where I stop looking and I went with my gut and just pick the
next tutorial that I found that seemed of decent quality this is something you
can apply to your data science learning process as well I firmly believe that
the majority of the courses out there for data science are very good and it
matters more that you start somewhere rather than choosing the perfect one
that might not actually exist I made a video about the best free courses that I
found and I've linked it above and below if you want more information on that I
also have a good relationship with 365 data science and you can get a discount
on their courses through my link below if you're interested the tutorial that I
found broke down solving the Rubik's Cube into basically seven different
steps each of these steps were reasonably manageable but again I felt
like it would be almost impossible for me to get through them all sequentially
at this point I remember the second epiphany that I had when learning data
science breaking things down into small and digestible components is the best
way to actually learn something you learn each one individually and then you
put it together at the end I knew I could understand each of the individual
steps and if I stopped worrying about the stuff that I didn't know yet it was
easier to focus on the task at hand each day I focused mainly on a single step
and I did a little practice you know just tying one or two or three of these
together breaking this big challenge into small and manageable problems
helped me not to get discouraged and to stick with the overall process each day
I was creating little wins that I could get excited about you know I'd solved
one or two parts and that was an accomplishment for me again data science
is no different you can transform the field of data science into a series of
little steps for example one step you could be trying to understand some
programming for loop in Python and another day you could try to understand
how a simple linear regression works after you understand how these tools
work they'll have a far easier time understanding how a while loop or a
multiple linear regression functions you can almost always build on the knowledge
that you accumulate as well it might sound super cliche but if you were to
climb Mount Everest you would do it one step at a time if you focus on making
the individual steps without looking up too often you
eventually reach your destination the last thing in my Rubik's Cube experiment
reminded me of was the importance of being patient with myself learning takes
time and most people will not get it right away
the last step of the process for solving the Rubik's Cube was so frustrating I
just couldn't get it at one point I got so frustrated that it really wasn't even
fun anymore I had to remind myself that challenging
myself is fun and that I'd eventually get it it's okay to put something down
and pick it back up again later if you persevere and are kind to
yourself in the process you'll get to the destination 99% of the time when it
comes to data science I distinctly remember reading the same page of one of
my textbooks like 15 times to finally just the networking topic I was focusing
on I learned many other complex topic topics before and I knew I was capable
of learning this at some point I hope that my experiment here helped you to
get past your own personal hurdles when learning data science if you enjoyed
this video please show it some love by hitting the like button and if you want
to see more remember subscribe and turn on notifications to be alerted when I
post my next weekly video until next time good luck on your data science
journey