Calculated Conversations: Learning AI by Building, With Kaggle Grandmaster Parul Pandey

AI leader Parul Pandey shares her journey from data analysis to Kaggle Grandmaster, discusses the ethics of machine learning, and advises aspiring data scientists to start with a clear project and learn the theory as they build.

In this edition of Calculated Conversations, I am joined by Ms. Parul Pandey, a Kaggle Grandmaster and a leader in AI and data science. Ms. Pandey's journey spans from making AI more accessible to children, to co-authoring a book on responsible AI, and even earning a spot as one of the top minds in the field. We discussed how AI is transforming education, the ethics of machine learning, and her advice for aspiring data scientists. Here is what she had to say:

You have worked in AI, written a book, and even earned the Kaggle Grandmaster title. What first got you interested in data science?

I have always had an interest in numbers, but my real experience with Data Science started in my first job. I was part of a team focused on the analysis and planning of the Power Distribution network. Back then, it was just called data analysis. But as I worked more and got curious, I started researching on my own and discovered that there was an entire field built around it, called Data Science. That realization pushed me to dive deeper into learning data science and machine learning.

Many people find AI intimidating. How would you explain its real-world impact to someone outside the tech world?

AI can seem intimidating, but it is already part of our daily lives. When you use Google Maps for directions, ask Siri for the weather, or get personalized recommendations on Netflix or Spotify, AI is helping make those tasks easier and more personalized. These are just a few examples of how AI is improving everyday life. That said, it is important to use AI responsibly, especially for high-stakes decisions, like hiring or medical diagnoses. We must ensure AI tools are used ethically and that humans remain involved to ensure fairness and accuracy.