Hi past, present or future data professional!

As the winter holidays approach, we’re entering a period of downtime for most orgs. Assuming your employer has hit goals (or accepted losses), allocated coverage for the slew of inevitable vacation requests and maybe even entered a “code freeze”, you’re entering data & tech’s slow season.

If you’re working, during this time you may be asked to do any number of “downtime” (actual free time, not data outages) tasks ranging from code refactors to documentation. In school, you’re likely preparing for or bracing for impact for final exam results.

Either way, this is the time of year professional engineers get the “other stuff” out of the way, including certification prep and completing any employer-mandated courses (I have 2 to look forward to by the end of this month).

This got me thinking about a question anyone investing in continuing education asks: What actually makes a good course?

Outside of work-mandated modules I have no control over, I lean on my prior journalism brain to “vet” courses according to the following criteria:

• Relevance: In a dynamic industry, I can’t condone taking a course more than a few years old unless it focuses on a niche tool or features prominent updates; anything over 5 years without a substantial update is a red flag
• Creator Credibility: Faceless content won’t cut it here; I need to know the person behind the knowledge. And most importantly I need to know they specialize in what they teach; I don’t want a generalized software engineer teaching data engineering
• Social Proof: Posted reviews are one thing. But I’m much more likely to take a course if it’s personally recommended by a colleague or friend in the industry; recommendations carry a lot of weight for more intensive resources like certification prep courses
• Applicability: I can’t just watch videos. I need some kind of sandbox or exercises that help me practice and apply new concepts. I like Google’s Quick Labs for this reason

And aside from these more concrete metrics, I’m looking for an instructor I want to learn from and follow, potentially, to multiple courses. One of the best ways to endear yourself to students, in my opinion, is to empathize with universal struggles.

4+ years later I still think about the SQL instructor that sacrificed a module in his highly rated course to talk directly to the camera about his confidence issues as a new dev, something I also experienced in my first year.

Just because someone has more knowledge than you currently doesn’t mean they didn’t start from the same foundation.

P.S. I’m thinking about creating a course in the new year. What do you need to know about data engineering that you’ve struggled to find elsewhere? Respond to this email if you have feedback.

Thanks for ingesting,

-Zach

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