Because computer science is a field of mathematics, teaching the shit employers want is categorically not CS.
Mainly though it is because schools are not interested in churning out employees as they are in creating researchers. Universities are research institutions which teach dumb 18 year olds so they have more money to spend on research and more researchers in the future.
Also all the interesting, high-level jobs at Google etc. do require a deep CS knowledge.
In computational complexity theory, a decision problem is NP-complete when it is both in NP and NP-hard. The set of NP-complete problems is often denoted by NP-C or NPC. The abbreviation NP refers to "nondeterministic polynomial time".
Although any given solution to an NP-complete problem can be verified quickly (in polynomial time), there is no known efficient way to locate a solution in the first place; indeed, the most notable characteristic of NP-complete problems is that no fast solution to them is known. That is, the time required to solve the problem using any currently known algorithm increases very quickly as the size of the problem grows. As a consequence, determining whether or not it is possible to solve these problems quickly, called the P versus NP problem, is one of the principal unsolved problems in computer science today.
While a method for computing the solutions to NP-complete problems using a reasonable amount of time remains undiscovered, computer scientists and programmers still frequently encounter NP-complete problems. NP-complete problems are often addressed by using heuristic methods and approximation algorithms.
Or N=1 which results in a balanced equation. Or it is a line of code and it doesn't have to be balanced, it just have to indicate that the new value of P is the old value of P times the stored valued of N.
wow, /sci/ is even stupider than /g/.
makes sense though.