Understanding of Algorithms and Data Structures

Essential for building efficient, scalable machine learning models, a strong foundation in algorithms and data structures is a must. This includes knowledge of sorts, searches, trees, and graphs, as well as understanding how to manipulate and store data efficiently.

Essential for building efficient, scalable machine learning models, a strong foundation in algorithms and data structures is a must. This includes knowledge of sorts, searches, trees, and graphs, as well as understanding how to manipulate and store data efficiently.

Empowered by Artificial Intelligence and the women in tech community.
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Rutika Bhoir
Grad Student at Umass Amherst

One tip that actually made a difference for me? Stop waiting to “feel ready” and just start showing up for two hours a day. I used to avoid DSA because I thought I had to be good at it to even begin. But once I stopped trying to do it perfectly and just gave it consistent time—things started to click. What helped me the most was using free resources like MIT’s intro to algorithms, Neetcode, and even ChatGPT to walk through problems when I got stuck. I didn’t always understand things on the first try. Still don’t, sometimes. But giving it regular time—even when it felt slow or frustrating—built the kind of thinking that actually helps in AI and ML work. Not just for interviews, but for understanding how data moves, how memory works, and how to build things that scale. So if you’re overwhelmed, try this: two hours a day, no pressure to be perfect. Just show up. Let yourself learn. That’s what worked for me.

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