Data Science is a form of statistics. Algebra II is a pre-requisite for statistics. How is replacing a pre-requisite with a more advanced class is a good idea?
When I studied statistics in university we studied clustering, regression, hypothesis testing, confidence intervals, visualisations, charting, general linear models... how is this different from data science?
Is it just because we have more computing power, so we rebranded it? Instead of doing frequentist analyses because those are easy to do with smaller computers, now we do more Bayesian stats, on bigger computers, and therefore call it data science?
Of course, since it was a professional course there is probably the assumption that students already know these things…
data science is more practical in a sense, you learn more to prepare real-life data for analysis.
also statistics coursework doesn't cover ML part (at least the stats course that I took)
> The core issue of the CMF’s “data science” section is that it claims to be discussing data science while it is actually discussing data literacy.
> ...
> The CMF is replete with statements like “high-school data-science class students can learn to clean data sets – removing any data that is incorrect, corrupted, incorrectly formatted, duplicated, or incorrect in some other way [...] High school students can also learn to download and upload data, and develop the more sophisticated “data moves” that are important to learn if students are tackling real data sets.''
It’s more of an Excel class with some basic math sprinkled in.