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Any tips on structuring trainings? Would love to incorporate some trainings this year for data science/data engineering.

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I follow "20 + 20 + break" approach. My father used it for 30+ years (professor of physics and CS).

It means 20 minutes of theory, 20 minutes of practice, 10-minute break. It can be 25 + 25 + 5, or something along these lines. I never do more than 25. The bottom line is that people are getting bored after more than 20 minutes of theory.

Good luck!

Thanks. How about topics? How do you choose which topics to cover? Or is this mostly led by clients?

I'd say mostly led by clients. But both of them were Ruby crash courses. Pretty much from nothing to getting up to speed in two days.

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