Where in the curriculum do you learn about what science is or what the scientific method is? Where do you learn what it means to do science, to be a scientist? When do you learn about the principles of reproducibility and falsifiability or how to generate and test hypotheses? (Statistical hypothesis testing is not science btw either. This is why there are no statistical scientists and statisticians do not call themselves scientists) What class teaches you the principles of experimental design (DOE) or what information needs to be kept in a laboratory notebook? (Of course I recognize that most data scientists and many actual scientists do not work in labs. However, the principles of lab notebook keeping guide scientists and ensure that their work is understandable by others and reproducible among many other things).
Based on what I just read the answers are nowhere, nobody, at no time, and none. A complete and thorough understanding of the areas I described is a pre-requisite to being a scientist and doing actual science. This is yet another reason why data science is not science and its' practitioners are not scientists. Data “science” is a useful tool of science but it is not science.
This is no value judgement and I do not suggest data “science” is somehow less valuable or worthy as a pursuit and occupation than science. I simply state a matter of fact. It does do a disservice though to all practicing actual scientists when persons who are not scientists claim that title for themselves. It dilutes and weakens the community of scientists and confuses the lay public even more as to what it means to be a scientist and practice science. This bothers me greatly and is why I continue to hammer on this point.
See this infographic I created for more on this
“Data Science Vs. Actual Science” https://medium.com/@dema300w/data-science-vs-actual-science-9a8b1b6c5ac4