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Lumifer comments on An update on Signal Data Science (an intensive data science training program) - Less Wrong Discussion
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Could you please elaborate with specific examples of times when Jonah's explanations were too abstract and not sufficiently practical?
This will be useful information for us, because we certainly want to identify areas in which our curriculum needs further improvement. My personal recollection of Jonah's lectures is that they involved a lot of example code, visualization, back-and-forth Q&A, and interactive exploration of real datasets in lieu of presenting, say, abstract mathematical proofs.
Along similar lines, what are some specific topics that you think were neglected in favor of more abstract but less applicable material?
I'm particularly interested in what material you thought was overemphasized in the curriculum--my impression is that all of the topics covered were very fundamental to data science as a whole. While one can express a valid preference for certain fundamental topics over others, I would be hard-pressed to say that any of the topics covered in the Signal curriculum weren't extremely industry-relevant.
That's a funny comment. It does exactly the same thing twice: Please tell us where we didn't do too well, oh, and you are COMPLETELY WRONG because we did everything very well.
In context, it makes a lot of sense for him to do that. He's working for Signal now, so presumably is interested in how to improve the program, and he was a participant at the same time as Fluttershy, so he got an impression of the program as a participant.
No, it doesn't. Continuing with the charitable interpretation, wearing these two hats at the same time is... difficult. Either he, as an employee of Signal, is genuinely interested in feedback, or he as a participant thinks Fluttershy is all wrong and making shit up because it was perfect for andrewjho (here he, of course, committs the typical mind fallacy, but that's a minor issue at this point).