Clinical Data Science For Non-Data Scientists Part 2: Resources For Bridging The Gap

It’s hardly a surprise that data science is one of the “it” careers and that more and more career paths need to be data fluent.

For several years now, I’ve held a top-down view of data science that might make me a lot less popular: learn data science, and I mean really learn it, and clinical data science will be a snap [mostly applying principles you already know; after all, to a computer, an int data type is pretty much an int whether it’s a count of the number of TVs sold at a store or a heart rate], the inverse is rarely true. I once had a colleague who is a statistician (as in real, Ph.D. holding, with more Greek symbols on his whiteboard than English type of statistician) who convinced me of a similar rationale with regards to statistics vs. biostatistics.

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