hello welcome to the channel data
science with Harshit
my name is Harshit Tyagi I'm a data
science instructor and mentor so this is
the first video of the channel where
we're going to discuss what exactly is
data science why has it become the buzzword that it is these days and how
should you get started what should be
the Learning Path towards data science
now what exactly is data science so is
it about creating cool visualizations is
it about statistics is it about coding
is it about writing complex machine
learning models what is it
so data science has simply put solving
problems and creating impact using data
using past experiences for example a
data scientist working at a product
based company would be working on some
new product recommendations or he or she
would be working on improving the
existing products or they would be
working on some data analytics platforms
which would be used by the internal
deans or the external teams so it all
started when in 2001 William s Cleveland
published his paper read the science an
action plan for expanding technical
areas of the field of statistics where
he combined data mining with computer
science and made the practical usage of
statistics a lot more technical we could
now use computing power along with
statistics and this amalgamation was
called data science
so now let's try to understand what the
data science space looks like so this
data science pyramid here is basically
explaining us what's the hierarchy of
needs or basically the skills that
comprise the data science domain now the
solution to any data science problem
starts off with the collection of data
which is placed at the bottom next comes
how easy is it to access the data and
how efficient is the data infrastructure
which is ensured by data engineers in
the second layer now once you have the
data infra set up the analysts explore
and transform this data to uncover
hidden patterns store analytics and
create visualizations that make the data
easy to read then comes scientists and
senior analysts who have expertise in AI
deep learning designing experiments for
a be testing you know so you can see
that the data size domain in itself
gives rise to several job descriptions
that you can aim for get an engineer's
data analysts machine learning
engineer's data scientists research
scientists core scientists they're a
bunch of opportunities that you can aim
for so why has data science become a
buzzword these days you see a lot of
news around data science based companies
and startups raising a lot of money
you see nearly magic gets fifteen
million dollars Alteryx acquires machine
learning startup feature labs companies
raising seed funding of 50 million
dollars and just to launch some machine
learning framework the list just doesn't
stop there's an immense number of
possibilities in data science with a
large number of investors ready to fund
these companies this is going to be the
future be it banking finance healthcare
agriculture gaming entertainment space
exploration self driven vehicles you
just name it so when it comes to
learning data science I believe that
there are four major subjects or four
major branches of data science
curriculum that an individual should
work on
so the first branch is programming tools
they recover what's Python how to
program in Python how to program and are
based on the language that you choose
then we learn about how to use notebooks
various libraries like numpy pandas
tensorflow Chara's etcetera then the
second subject is data engineering where
we learn about how to engineer our data
how to extract it learn about writing
SQL queries exploratory analysis data
wrangling databases and api is the third
subject is mathematics and statistics
where we learn about linear algebra
stats, probability hypothesis testing AV
testing how to design your experiments
the fourth and final subject and branch
is called algorithms and systems where
you learn about machine learning and
deep learning algorithms how to build
recommender systems and other concepts
and all of this you have to practice all
these concepts in the form of projects
solving real world problems so now we
have understood that there is a lot of
interest in becoming data scientist and
for good reasons high job satisfaction
and high demand high salaries and high
impact so how should you get started so
a quick Google search on data science
will give you a plethora of resources to
learn from there are podcasts forums
blogs articles online courses self
directed curricula bootcamp so there are
lot of resources to learn from but not a
single resource cover the entire space
so with this channel I am trying to
cover the best of all these resources
and I am trying to cover the entire data
science space the four branches of data
science curriculum and all the concepts
mentioned in the data science pyramid
not only that we would learn from data
scientists working at Google Microsoft
Amazon and such big companies and learn
from CEOs what day look for data science
and what they look for in data
scientists so I'll be starting off the
four series on Python programming
directed towards learning data science
so do subscribe to his channel as you
would not want to miss any of the
content coming ahead and also make sure
that you like this video if you found it
useful and you can connect with me on
all these social media platforms so make
sure that you connect the me on LinkedIn
connect with me on Instagram where I
post a lot of stuff on health and
wellness
I mean connect with me on medium where I
read a lot on data science statistics
mathematics so looking forward to all
these series coming out ahead and see you
in the next video bye
