in the future there are going to be two types of people one people who know how to use AI smartly
two people whose job will be automated by AI I definitely don't want to be in the second
bucket and neither do you so in this video I am going to share how I have been adopting AI
specifically Chat GPT as part of my daily job as a data scientist so you can learn from it
the tips and hacks that I'm going to share can be applied to any jaw family including coders
data scientists data analysts software Engineers so keep watching for those who don't know Chad
GPT is an AI bot which basically talks to you like a human and I've been using it as a tutor
and a personal assistant chat GPT and its competitor like Bard are not going anywhere
so it's about time that we get smarter than all of these chat Bots a quick disclaimer don't put
any of the work information that is intellectual into chat gbt check your companies and schools
guideline before using chargpt it goes without saying be responsible when using charge GPT
so in this video I'm going to share four ways you can use chat GPT as a data scientist number one
coding for coding I've been using it primarily for two use cases one is to write new code and second
is to debug so for writing new code chat GPT does a really really good job for writing simple code
for simple questions it is not that great with the complex problem and more logical thinking
but it does a really good job of giving you simple code Snippets that you can use in your work for
example let's say I'm working on a project where I have to create an A B test here I want to create
a sampling group of control and treatment groups two groups with A and B and I want to have equal
sample size in both groups with randomization so here I can ask chargpt to write a code for me that
will help me do stratified sampling create sample A and B group stratified on Revenue so basically
here it started writing the code for me it's using the train and test split which is pretty common in
machine learning data sets so here in this example I know what exactly looking for I understand how a
b tests work and then I just get extra help from chat DPT to write the code obviously I can write
this code on my own but I want to use that time somewhere else so I can use chargeability here to
kind of help me write this code faster the second area in coding is debugging so I've been using it
for debugging purposes let's say if I'm running into an issue with my code where I'm getting an
error I am trying to figure out what is the issue typically I would go to my co-worker and have them
look at my code alternatively I can go to chatgpt and save the embarrassment and basically ask the
AI if what is wrong with it fine bug in this python code for linear regression so this is a
code that I had already written and if you look at the code closely you can find the bug in the
last three lines this is a very simple test of course in what I've noticed is that chat repeat
it does really well with simple questions but it doesn't do a great job with complex but in this
case it's able to find that issue and it's able to to give me the correct code second I've been using
it to prepare business communication a big part of the data science job family is communication
and storytelling that includes writing documents creating slides explaining to stakeholders asking
the right set of questions doing analysis and then explaining your analysis in words in simple
English words and this is where I've been using chargeability and it's been really really helpful
in that sense for example a lot of the times I have to as a data scientist I have to work with
business stakeholders most of those people are non-tech audience so a lot of the times I have
to translate that technical language into non-tech language here I can spend time on my own to figure
that out but I can also use chat GPD to speed up that time that is going to take me and ask
it to simplify it for me for example one of the models that I use quite a bit is causal impact for
experimentation space specifically on experiments that cannot be done with the control and a and
b design so here I use causal impact quite a bit but a lot of the times I struggle with explaining
it to stakeholders so here I use chargpt to simplify what is causal impact in a very simple
language for those who don't know causal impact is basically a pre and post statistical model for
understanding time series data for understanding the difference in Time series data in the pre and
post period and it's basically a model in r that you can use so here let's say I'll ask chargpt
explain causal impact model in simple language create a summary for plot one two and three that
spits out here it did a wonderful job explaining what a causal impact does and I'm pretty sure if
I were to share this communication with my business stakeholders they would be able to
understand it and not only that if you are new to causal impact and you're trying to understand and
you need somebody to guide you you can actually use chant repeat to kind of like look at the
simple explanation so simplify Concepts has been a big use case for me with chargpt and you can
use it for learning new Concepts or you can use it for simplifying existing Concepts that you
know or your communication with stakeholders and business people of course as we get more
and more surrounded by AI we do not want to be too dependent on AI that we lose the side of the
brain where we actually do The Logical thinking because as AI progresses a side of our brain where
logical thinking happens is going to become more and more important because shared GPT tool and
any similar models out there are going to be able to do simple tasks very quickly and that's where
our cognitive thinking our logical thinking our analytical thinking is going to become more and
more important one of the platforms that enables me to think more logically is brilliant.org
who is also sponsoring this portion of the video brilliant.org is an awesome tool for learning stem
subjects interactively in fun Hands-On way they have several learning paths including data Science
Foundation which covers probability fundamentals and builds up to using data in predictions
experiments and neural network the problems are super interactive and structured in a way that
help me understand difficult Concepts in a logical way it is a great way way to keep your mind sharp
especially in the world of AI as the information Gap continues to close to try brilliant.org free
for 30 days visit brilliant.org Sunday's college or click Link in the description the first 200
people to click will get a 20 off Brilliance annual membership give it a try you might like
the interactive style of learning which is one of my favorite ways to learn new things the Third Way
that I've been using chat GPT as a data scientist is to help me analyze data let's say I'm working
on some new data set that I don't fully understand I can spend a few hours doing exploratory data
analysis short for Eda or I can ask chargpt to do it for me in less than five minutes for example
I have this data set that is from my personal project that I've used in the past so I basically
it's a bright share data and I'm gonna copy paste it and I'm going to put it into chat GPT and ask
it to explain the data for me so here as you can see like it's doing a good job explaining it's
going into detail for each column the second thing I asked it is to give me descriptive stats and
here it's generating that for me as well again be smart about it you can rely on that GPT for
basic stuff but you still need to fully understand what the data does what are the different column
means you still need to have the basic business understanding behind the data set to be able
to actually use it it's super powerful tool for summarizing your data quickly for example if you
want to do some descriptive analysis on your data you can do that let's say if I want to find the
mean value of column act column Revenue I can do that I can also input a data into charge GPD and
ask it to create visualization I can also ask it to create tables for me from the data sets I give
it so there are so many use cases and I should probably cover it in a separate video what are the
different ways to analyze data with charge gbt or any of the similar tools including Bard the fourth
way I've been using cha GPT as a data scientist is for interviewing and I'm going to tell you
like this is literally literally literally this is my favorite part about working with Chad Deputy is
the interview prep there are so many use cases that I can talk here but I'll share a few uh
right now and no I do not mean that use it during the interview I mean use it to prepare for the
interview so it's like before the interview so like don't that's cheating if you are using Ted
Deputy during your interview it's cheating so don't do that I do not support that so some of
the use cases that I've used it for interviewing purposes or interview prep purposes uh one is for
coding so let's say I'm practicing on lead code or strata scratch and I have a free version there
are certain questions that Solutions are only accessible through the paid version so here what
I do is I actually put the question in in jet GPT and ask it to give me a solution so for example I
practice coding on this website specifically SQL and python questions I have a free membership
and there are only a set of questions that are available for free the other set of questions
are available you can view them but you can not see the solution so here can't believe I'm
saying this but I actually used I didn't I should have bought the membership but I didn't buy the
membership but I actually used those questions and put it into jazz GPD and get asked it to give me
a solution and it worked out perfectly for me in the future I will consider getting a membership
please don't come after me but this this was great the second bit that I've been using it to simplify
Concepts so here I've used Chad GPT to basically review the fundamentals and take notes example
here one of the one of the questions that I Was preparing for an answer for in when I was doing
interview preps is in classification regression there's the concept of precision versus recall
and this is one of actually one of the favorite questions in machine learning interviews where the
interviewers like to us like how do you explain precision versus recall or they will give you a
problem and then they will ask you to like what's the Precision and recall here of course there's
like some business context behind it but like the basic fundamentals of what precision and
recall is so here I actually use chat GPT to do so many variations because I realized that
I I can mix that up in interview setting and I wanted to get a very dumbed down version no shame
in it I actually did ask Chad Deputy to explain precision and recall to a child and then later
I also found some YouTube videos that were like super helpful in explaining but this is just to
give you an example that I have used it for like super basic fundamental concepts in statistics and
machine learning in data analysis data science to basically to review the foundations besides what
I've shared so far there's so many other ways to use chat GPT in your day-to-day job at work
and outside work including writing documentation writing emails summarizing meeting notes writing
animal performance reviews writing peer feedback automating Excel sheets using VBA code I cover
most of these use cases in this video so watch this next let me know in comments how you have
been using chat GPT have you tried anything from the list that I mentioned or any other creative
hacks that you would like to share thanks for watching I'll see you in the next video bye