Comet Office Hours: Recap for June 27, 2021

Welcome to another recap of the Comet ML Office Hours, powered by The Artists of Data Science!

It’s hard to believe that June is almost over—which also means that I’m approaching the 2-month mark in my role as Head of Community at Comet. It’s been incredible to feel so embraced and welcomed both by the wonderful Comet team and by our community of talented, thoughtful data scientists and ML practitioners.

In that vein, these weekly sessions are something I really look forward to—they help me better understand the mindsets of aspiring data scientists, and I also always enjoy the philosophical bent to the conversations.

If this sounds like something you’d enjoy, as well, 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), but I’ve summarized a couple of my favorite exchanges below.

I just finished a Data Science Bootcamp…now what?

Data science bootcamps can be a great way to learn a lot of the foundations of this growing field, but they aren’t silver bullets—it really comes down to your ongoing investment in learning and solidifying those foundations.

Guest Suman Gautam raised this “what’s next” dynamic, and the group had some great suggestions:

• Projects, projects, projects: This is all about applying your knowledge to real-world problems and situations (as much as possible). In other words, the skills you’ve learned cannot remain abstractions…they must be put to use.
• Professionalism in your projects: Extending on the concept of projects, there’s also the importance of building a professional-looking portfolio with well-structured code, detail-oriented documentation, and more.
• Don’t forget the “simple” stuff: It can be tempting, as you increase the complexity of your projects, to set aside the basics. In the job hunt, you’ll be served well by remembering and showcasing those basics—a lot of entry-level jobs will demand these basics, anyways.

Check out the clip below for even more advice and suggestions from the group:

Learning technncal DS concepts when coming from a non-technical background

As the data science profession continues to grow, and opportunities to enter the field and reskill expand, lots of folks with non-technical backgrounds are exploring the industry’s possibilities.

But there are a lot of specific challenges when trying to reskill in this way. The group shared some thoughts on ways that technical learners can approach this dynamic and get a leg up on the competition.

Resources Mentioned

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.

• Anki (flash card software)
• Blockchain Data Analytics for Dummies, Michael G. Solomon
• The Model Thinker, Scott Page
• How to Read a Book, Mortimer J. Adler

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!

Register for Comet Office Hours

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!

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