How Harshada became Data Influencer

In this episode of Weekly Success Stories, we feature Harshada Mali, a part of INSAID GCDAI 2019 cohort.  

Harshada is a Data Science influencer and an exemplary student achieving lots of success. Let’s take a look at her journey as a Data Scientist and the tips she has for beginners!

Q1. Tell us about your current role and background?

I’m responsible for analyzing the data and using the data for developing machine learning models. And I do have to scale them across using distributed systems. 

Q2. Why did you choose to learn Data Science?

I’m a very curious person and when I came across Google Maps, I wanted to know how it works?  So, I researched about it on Google and understood that it’s machine learning. Eventually, my curiosity for machine learning increased and I started learning more about it. 

Then I came across INSAID and that’s how my Data Science journey started.

Q3. Could you share a little more about your journey as a Data Influencer?

I started my journey in 2020 as a Data Influencer.

At INSAID we have to work on some projects during the course. So while working in these group projects, I shared my notes with my cohorts, and they found them very helpful.

They often asked me about my notes, and that that’s where it started out, influencing people or helping people through my content. And now I’m also helping thousands of data enthusiasts through my content by sharing it across social media.

Data Scientists are really growing a lot and I’ve seen that in this year itself computer vision applications have taken good adaptation across various industries. So we have seen applications like human pose estimation, even object or vehicle detections on a very high scale.

So in NLP part, Google has released Google Lambda, which is language, model dialogue applications which kind of is an interaction with the machine itself.

You can interact with machine, regardless of the topic you have. This in itself is a huge trend and achievement in Data Science. 

Q5. Tell us the challenges you faced in your Data Science journey?

My Data Science journey started in 2019 and I also joined INSAID the same year. The challenges I faced were not setting realistic end goals.

In Data Science there is lot to learn and we have to learn it step by step so its very important to keep deadlines and specific goals of what to achieve. 

First of all, its very important to have community you work with because it gets easier to help each other and work together. The challenge that I had was that I faced a lot of problems while explaining.

One of the challenges I faced was not asking for feedback. It is very important to ask for feedback.

Q6. Why INSAID? How did it help you?

INSAID really helped me a lot in my Data Science journey. They made Data Science interesting and more approachable.  It was not something like a mountain to climb on. It was a very small thing. And it was very much interesting. 

We went step by step which made it much easier.

INSAID has one of the best faculty here. They are very supportive along with the academics team that helped me in my ups and downs. 

Whenever I had a doubt they replied to me well and helped me through all the challenges that I faced with the projects or even with the content. So, I’m really thankful that I joined INSAID because they are providing you much more than what you asked for. 

Thanks to them that we also have industry interactions so we have knowledge of trends or what applications we have to go through and what projects we should do that would really help us grow in career and as an individual. 

Q7. What advice would you give to Data Science beginners?

The advice that I would give is to start with coding. Coding is a must to become a Data Scientist but don’t think that coding is very hard. You can start with R or Python. But I would suggest you Python because there are lot of resources and python community is very helpful.

I would not say it’s easy but it is very approachable.

You also have to learn how to deal with the data. So you will be learning how to deal with it. There are different packages like NumPy, pandas and matplotlib which will help you to grasp the concept very easily, even when you’re working with deep learning concepts. So, it’s very important to go step by step.

Third you have to learn ML i.e. Machine Learning and only then go into deep learning. Don’t jump into Deep Learning because that may bring you a lot more difficulties in some mathematical concepts. So it’s very much important to go step by step. 

We hope you found this success story interesting. If you have any Data Science questions, please fill this form and we will get back to you.




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