The typical holder of a four-year degree from a decent university, whether it's in "computer science", "datalogy", "data science", or "informatics", learns about 3-5 programming languages at an introductory level and knows about programs, algorithms, data structures, and software engineering. Degrees usually require a bit of discrete maths too: sets, graphs, groups, and basic number theory. They do not necessarily know about computability theory: models & limits of computation; information theory: thresholds, tolerances, entropy, compression, machine learning; foundations for graphics, parsing, cryptography, or other essentials for the modern desktop.

For a taste of the difference, consider English WP's take on computability vs my recent rewrite of the esoteric-languages page, computable. Or compare WP's page on Conway's law to the nLab page which I wrote on Conway's law; it's kind of jaw-dropping that WP has the wrong quote for the law itself and gets the consequences wrong.

[–] colmear@discuss.tchncs.de 1 points 6 hours ago

I‘d honestly be interested where you are from and how it is in other parts of the world. In my country (or at least at my university), we have to learn most of what you described during our bachelors. For us there is not much focus on programming languages though and more about concepts. If you want to learn programming, you are mostly on your own. The theories we learned are a good base though

[–] irelephant@lemmy.dbzer0.com 2 points 20 hours ago

I meant the guy in the picture, but thanks anyway