Comet Office Hours: Recap for August 8, 2021
Welcome to another recap of the Comet ML Office Hours, powered by The Artists of Data Science!
This week, I want to kick things off with a really exciting announcement. Harpreet, our fearless leader, incredible host, and relentless learner, is going to be joining the Comet team full time at the beginning of September!
He’ll be working as a Data Scientist for our Growth team, where he’ll work on all kinds of projects to help us build more robust solutions to some of the most pressing challenges in DS and ML, all while sharing his journey with the community. We couldn’t be more excited to welcome Harpreet into the Comet family! 🍾 🎉
Onto our weekly Office Hours session—a couple of longer segments to share, only because the conversation has been getting so lively and engaging.
The two I chose this week, in fitting fashion, explored career dynamics in the field—from the necessity of advanced or more formal education, to strategies for getting your bearings in a new role at an organization you’re unfamiliar with.
As a reminder, we’d love to see any and all of you at these hourlong sessions—so feel free to register for upcoming Office Hours sessions here!
As always, there’s a lot more in the full session (which you can find on Harpreet’s YouTube channel), so be sure to check it out, alongside all of Harpeet’s other excellent content.
Is formal education a necessity for a career in data science or ML?
You know a thread of discussion is going to be good if Harpreet kicks things off with something like, “At the risk of inciting a riot…”
But in all seriousness, we got a range of interesting answers from the group, including the importance of differentiating the kind of role you’re seeking, some of the tangible networking benefits you can get at a traditional educational institution, and, alternatively, where you can find community and networking opportunities in more distributed environments (like our Office Hours sessions!)
Check out the extended clip below for more takes—and counter-takes—on this issue that seems to continually be evolving.
Finding your footing in a new role
Another solid question that I thought led to a really compelling discussion came from Office Hours regular Asha, who asked for tips and strategies for getting started in a new role at a new organization—especially when your new employer is throwing you into the deep end before giving you a chance to orient yourself.
In response, the group touched on a number of possible approaches, but there seemed to be a few themes:
- Ask questions—find folks who’ve been around, and don’t be afraid to ask them for help, no matter how simple your questions might seem
- Find ways to embed yourself in the overarching challenges the organization is tackling or trying to solve
- Make quick assumptions—essentially, “be wrong quicker”. Nobody expects you to have everything figured out day one, but if you take the approach of making fast assumptions and being flexible with them, then you’ll have some data to work with
In addition to the wonderful back-and-forths throughout the session, there were a whole lot of interesting resources mentioned, both by Harpreet and many of the attendees. Here’s a quick list, in case you’d like to check out what is capturing the community’s attention.
- Deep Learning Illustrated, by Jon Krohn
- Grokking Deep Learning, by Andrew Trask
- “One Concern” and “Urbint” — resources for ML in civil engineering
Enjoy the Conversations Above? Join Us!
We run these virtual Office Hours every Sunday at 12pm ET (New York, NY). Completely free to attend and participate, and we’d love to see any and all of you there, help address any questions you might have, and just hang out and talk all things data science and machine learning!
One last thing…
We recently launched The Comet Newsletter, which offers a weekly inside look at all things data science and ML, featuring expert takes and perspective from our team. We have big things planned for both Office Hours and the newsletter, so be sure to subscribe if you haven’t already!