>>11806138This is retarded, you dont need half of the tech specific stuff to be a good data scientist.
But you need a hell of a lot more fundamental knowledge in mathematics and neural networks.
To put it into perspective the "Fundamentals"+"Statistics"+"MachineLearning" should take up around 70-75%. You dont need to know the case-specific techs and methods so well, just know that they exist, so if you are in a situation you need them you can pick them up and learn them on the go.
I would also add a +10-15% as "specification" where you delve into a specific matter and really get to know it. For me that is NLP with dynamically adapting parsers.
