My first steps into Data Science: Part 2 with Deepesh Wadhwani | Ep#19

Welcome to Episode 19 of Data Science & AI Weekly!

Listen to the professional journey of one of Accredian’s Top Faculty, Deepesh Wadhwani as Manav, Accredian’s Chief Data Science Mentor, interviews him about his career journey in this Part 2 of Episode 19.


[00:09] Topic of Discussion: How to choose the right Data Science program?
[00:40] Series Overview
[01:05] Welcome Deepesh! Senior Faculty at Accredian
[01:17] Deepesh’s Data Science education
[01:30] First Data Science Project
[03:21] What to look for in a Data Science Program?
[05:38] Wrap up!
[06:00] Learn more about Data Science at

You can follow the podcast here.

Manav: Welcome, everyone. My name is Manav. I’m the Chief Data Science Mentor at Accredian and what I’m going to do is since we have in this exclusive episode of Data Science and AI Weekly, we have Deepesh with us.

 What I want to do is ask him questions about how he got started in Data Science, what are some of the tips that he has? And what are some of the things that we expect from our students in terms of learning and succeeding in Data Science so if you have not subscribed to our channel, just subscribe immediately.

You will never miss an update when we release the next podcast and if you have not tuned in to the other episodes of this podcast, the other 18 episodes that we have done, just go to the description you will be able to see the playlist in the description itself. So, with this, let me just welcome Deepesh. Welcome Deepesh to this podcast and very, very glad to have you!

Deepesh: Thank you so much, Manav. I’m very happy to be here!

Manav: So let me step again, back. You were working in Tata Motors, you worked on this project, then when did you formally start moving towards Data Science? And when did you formally discover that Data Science is possibly a direction that I should move into?

Deepesh: That happened after my second project. My second project was given to me by my own family. So my family owned a few businesses and I was given a single project, start an FMCG firm, in order to sell it off in let’s say 18 months’ time, so build it, set it, also build a business and earn profits from selling it, not the operations. So I had to make a business that was more lucrative than any other FMCG business available at that point of time for anybody to tap into.

And what I did was, I constructed the business in such a manner that every data point was recorded. I used sensors, I used a basic counter I used left, right and center everything to record data, I used to give out different pamphlets for different areas just in order to see how many of them actually come back to judge if the market, if my market will be lucrative in some area than the other, so I can have a marketing strategy built around that concept soon.

Manav: And I think this is a great way of doing what we today call A-B experiments, right? So also doing different pamphlets in different areas and seeing which is working instead of like doing the same thing and not knowing what is working. So this is like the offline version of A-B testing.

Deepesh: Absolutely. Right.

So but a mechanical engineer back then didn’t know what AB testing was, didn’t know anything about machine learning, and still was able to do the most basic, most intuitive thing that machine learning does, he was able to make business sense out of data. And after the project was complete, I formally joined a course in which I did my sort of master’s in Data Science.

Manav: So let’s talk about this program that you did, which year did you get enrolled in? And since you come from a business family, how did you realize that this is a program that you want to formally join? Right? And I think you did the program from IIM Calcutta. Yes. Yeah. So let’s talk a little bit about your journey there.

Deepesh: So after I finished the project, which my family gave to me, I didn’t even know the keywords to search on Google. I didn’t know the word Data Science back then. So I was searching for programs I used to search how to analyze data. What can I do with data kind of things, and I am not sure if it was an internet search or if it was one of my conversations with my colleagues, somebody popped in the name PGDBA- Postgraduate Diploma in business analytics.

It was a course newly introduced back then, probably first or second of the nation. Now, all a lot of colleges offer Data Science programs at even a bachelor’s level/ at masters level. We teach awesome Data Science here at Accredian so we are all aware of Data Science programs.

But that was probably the first or second program that was started in the country. And I searched for it. I enrolled, there was a written test, took into, got into. I never looked back.

Manav: Yeah, very good. So now, which year did you finish the program? And what was your journey after that?

Deepesh: So I started my program in 2016. And it took two years for me to get my PGDBA degree and in 2018, by the end of 2018, I had already worked.

During the program itself. I was working with Mitsubishi Fuso, so I was designing a pricing strategy for them, how to price their spare parts. Once that was over, I came back and I started working with Wells Fargo.

It’s an American bank, and I was a Credit Consultant. So we used to create an equation that predicts will a person default or not?

So again, it is basic logic. If a person defaults, we should not give them the money, that’s bad business. So, until we are able to predict will not be able to make that business decision, and hence the importance of credit risk modeling team.

Manav: Alright, so I’ll talk to you more about your teaching aspects and what are some of the expectations that you have from the students now that you teach. 

We will continue quizzing Deepesh about Data Science, about how to successfully ensure that you become a Data Scientist, etc in the next episode which is going to be Episode 20 of Data Science & AI Weekly.

So what we’ll do is we will wrap up this episode here and we will see you in the next episode of Data Science & AI Weekly. Thanks for tuning in. And if you have any questions that you want the page to answer or if you want us to answer just leave your comment in the comment section. We will surely make a podcast on that as well. Thank you very much, everyone, for tuning in and this is Manav signing off.

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