\>___> I'm going for a master of statistic and thought the premise in the beginning was weak at best. And then toward the middle of it, it basically said data

\>___> I'm going for a master of statistic and thought the premise in the beginning was weak at best. And then toward the middle of it, it basically said data science is a marriage between stat and comp sci. Congrats I have comp sci as an undergraduate. I think it's weak at best. Data science is a jack of all trade and master of none. I disagree that it's just cs and stats, I know it might be pedantic but it also ML which involve math that is a bit more than stats. Math it's either right or wrong. Stats you can kinda bend that in such that it's close enough. Some may say what's the difference. This article doesn't address the difference but from what I've gathered Neural Network will tell you or categorize stuff likewise with KNN, but you won't gain insight into the WHY it is categorized that way and this is where statistic can tell you why. From lurking in the subreddit /r/statistic, Bayesian will tell you why but NN will not. You still need statistic. It's just that this is a new field and many people don't have the depth to grasp what's important. It's like hyping up a nosql database and promising many things and get people to adopt it. Eventually they'll realized that it's just broken promises and they're stuck with it. In this case, the industry can just get smarter and have better idea of what they really need.