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This is Five-Minute Friday, on how The Learning Never Stops.
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I recently received a note from Nikolay Kurbatov, a Russian data scientist and AI product manager from Moscow. He said: “I just wanted to share that I’ve completed 40 of your ML Foundation course lectures already and the course rocks! One of the best Foundation courses I’ve taken, thank you very much for your effort and I can’t wait to see the Calculus videos.”.
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So Nikolay’s referring to my Mathematical Foundations of Machine Learning Udemy course, which is a work in progress. I’ve finished the first of four subject areas, Linear Algebra, and am currently releasing the second subject area, Calculus. When I shared with him that I happened to be uploading the first block of Calculus videos that very day, he replied to me that, “That’s perfect news. Also,”, he says, “I found out that the more I learn about the data science field, the more I understand that the learning path for the field is endless. I mean that you always find some new stuff to learn.” He says that he’s “heard a couple of times during the SuperDataScience podcast and on the other podcasts as well, that having a PhD in the data science field doesn’t mean the learning curve has come to an end, sometimes – quite an opposite. That’s amazing, but also mind-blowing and demanding emotionally.”
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All of this was interesting for me to hear because I too have often found the breadth and complexity of content in data science, as well as how quickly it changes, to be overwhelming. No question that a PhD doesn’t help. Indeed, as a PhD holder myself, I can assure you that it only makes you a specialist in a very narrow slice of data science and, if anything, it makes you acutely aware of how little you know even about that very narrow slice — forget everything outside that slice where you don’t even know it well enough to know how little you know about it!
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The point I’m trying to get to is that by choosing a data science career, the learning will never stop. That’s a big part of what’s exciting about it, alongside how impactful the vocation can be. There’s a fine line between excitement and stress, and so I hope all of you can find yourself on the excitement side of that fine line. Even the biggest-name data scientists at the most eminent institutions are experts at only a very narrow slice of the entire field, so there’s nothing to be stressed out about. The more experienced you become in data science, you appreciate that the reality of the field is that nobody has mastered all aspects of it and thus there’s no need to feel stressed because we’re all in the same boat.
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All right, so the bottom line is that the learning in a data science career will never stop. Relax into it, my friends. And catch you on another episode at the SuperDataScience podcast, very soon.
