In Talks with Radhika Mirani I Accredian Spotlight

A junior software developer, Radhika Mirani was always intrigued by the world of data science and machine learning models. She wanted to pursue a career in it for the long haul. So, when she came across one of Accredian’s ads, she took the opportunity and enrolled for the Global Certificate in Data Science (GCD) program at Accredian

In this interview, let’s see what interests her the most in Data Science and how her learning experience has been at Accredian.   

Question 1: Which program & batch are you part of at Accredian & tell us more about your current work profile?

Radhika: I’m a part of the Global Certificate in Data Science (GCD) program, April 2020 batch. I’m a junior software developer at Tata Consultancy Services.

Question 2: Walk us through your career journey & what got you interested in Data Science & Machine Learning?

Radhika: I’m still a fresher working as a junior software developer in TCS. I’ve always been very intrigued by recommendation systems since college. I remember we had a few introductory classes related to data science in our college studies last year. And I found those concepts very engaging. I think that sparked my interest in this field first. 

Since then, I have been regularly reading small articles on data science and AI. This kept me hooked. I wanted to get started with data science and machine learning models, but I didn’t know where to start. So one day, I remember a relative sent me a screenshot of an ad posted by Accredian. And a few months into the course, I thanked him for telling me about the institute.

Question 3: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at Accredian so far?

Radhika: I learnt the most commonly used packages of Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn. I have not mastered anything yet. I am just beginning to explore.

Question 4: What were some of the initial challenges when you got started on your Data Science journey, and how did you overcome it?

Radhika: One of the biggest challenges in learning data science and machine learning models that I faced was overcoming my inhibitions. I was well-versed with Python’s basics, like the syntax and all, before joining Accredian. As I do come from a programming background, I knew coding wouldn’t be a problem. But it was statistics that gave me a scare.

I was well aware that I would have to work very hard in stats to rise to the standards expected from a good data scientist. And, I have to say that the mentors at Accredian have been incredibly supportive. They have welcomed all questions, and they genuinely believe that no questions are stupid. This has helped me grow.

Question 5: What is the goal of Data Science?

Radhika: The goal of data science is to find hidden trends and patterns from the available data. These trends help us with powerful insights which, in turn, contribute to business growth. 

Question 6: What are the current trends in Data Science that you are most excited about?

Radhika: One of the things that excite me about data science applications and machine learning models is the recommendation system. It is the accuracy of recommendation systems that is both exciting and scary. Another exciting trend, which I’ve seen grow a lot in the past few years, is computer vision. The way systems can detect and identify objects and take relevant actions is just fascinating. Just a few months back, I’d seen a model demonstration on LinkedIn, which could detect whether people are wearing masks or not. Now that is something.

Question 7: Which are some of the blogs that you follow?

Radhika: I’ve subscribed to a few YouTube channels like Python Programmer, and I follow data scientists like Eric Weber, David Langer, and Steve Nouri. 

Question 8: What is your advice to anyone wanting to start a career in Data Science?

Radhika: I would like to give a simple piece of advice that has helped me in my journey. And that is to take small steps in the beginning, to avoid getting overwhelmed by the vastness of data science and machine learning models. 

Take more significant strides and increase your limits only after getting comfortable with the basics. And, it’s okay to not be a good at coding or stats. These skills can be worked upon and developed over time.

This was a conversation with one of our GCD students – Radhika Mirani. 

If you want to read more such interesting student stories, check out Accredian Spotlight.

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