That, I do not know. I was an art major 
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I never took Calc and now I work on computers for a living (for over 20 years!).
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I took math past Partial DiffEq and I don’t work on computers 
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As an aside, I’ve thought about going back to math in my 40s and trying to learn calculus and then I ask myself if I have a reason to do so, even if I could easily figure out how.
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In my line of work, I definitely need it. Calculus and DiffEq are important for circuit design, especially related to load balancing, filter design, communications systems, etc.
As far as figuring out how, I realized that calculus was needed when I tried to do areas and volumes for the first time. Surely these aren’t just equations that some smart person came up with that we all have to memorize now. There has to be a reason why the volume of a pyramid is 1/3 base times height, or why the volume of a sphere is 4/3 pi times radius cubed. If asking questions wasn’t suppressed in public education, we could start teaching calculus starting in third grade. It is not as complicated as algebra, which is taught starting in middle school.
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I’m not down on people learning to weld and fix cars (hell, I’d love to learn to weld.) But I too, am very down on this idea that keeps getting pushed forward that vocational training will somehow magically solve what turn out to be problems caused by deindustrialization and automation.
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I’m torn. On the one hand, these jobs need more respect than they get. Techs should not be seen as lesser engineers, especially since most engineers can’t or won’t do tech work. On the other hand, manufacturing is being outsourced more and more, so the jobs just aren’t there.
Have you heard of the Cerulean Collar jobs that Neal Stephenson wrote about? Basically skilled labor geared more toward the arts than traditional blue collar labor. An interesting theory, but these jobs are currently so few and far between that they don’t get to have a collar yet.
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Five frickin’ semesters of higher math and I have never used any of it… And I am not good at math, so it was painful. I took the final course four times before I found someone who could teach it to me (dropped it the first three times, so I didn’t have to pay for a course I wasn’t going to pass).
I picture the person setting the computer science degree requirements as having the level of real-world experience personified by… Betsy DaVos.
“Oh, computers are mathy, right? You have to know math to use computers!” :headdesk:
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It is a matter of numbering convention, as well as credit-hours for the course. I’ve taught Calc in universities where it meets for 3, 4, and 5 hours/week, obviously this has an effect on how many semesters it takes to get through the material. It also becomes problematic from the POV of how credits should transfer.
That wasn’t really my suggestion. I’m all for removing barriers to attending college (I was myself a 1st-gen college student on full scholarship), but I’m also in favor of having a rich ecosystem of curricular choices as opposed to the kind of homogeneity too-streamlined articulation imposes on some programs.
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Never change, Dobby.
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Oh there’s definitely some math that computer people should know, i.e. graph theory, algorithms, sentential and predicate logic. But notice that all of my examples are parts of what’s called Discrete math, and calculus is inherently about continuous things (other than the sequences and series that gets covered in many calculus sequences). So, yeah, :headdesk:
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And the understanding of which requires Calculus. If you need to know how rapidly an algorithm converges, and the formula arises as the nth partial sum of a series, the formulas for estimating the error between the nth partial sum and the actual sum are generally given as integrals. Likewise, if you are comparing rates of convergence you will find yourself needing limits, and might find yourself needing l’Hopital’s rule.
Similarly, if you are doing even discrete probability - for example, computing the expected value of a random variable with a geometric distribution - the way you do it is recognize that the series formula you get is the termwise derivative of another series whose sum you know.
Not everyone who studies CS needs this stuff, of course, but being exposed to it gives students more opportunities to pursue different paths as they move through their training.
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You should do it. I did and can’t say I found it difficult. I am 50. I’m now studying analysis. I find it fun. Wish I did pure maths in college.
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I look that stuff up when I need it, just like I look up coefficients of elasticity when I’m coding for polymer production by giant robots, or specific impulse when I’m coding to sample thrust transducers for static testing spacecraft propulsion, or HIPAA regulations when I am coding for secure data transfer to hospitals, or SOX when I’m doing work for the CFO of a stock brokerage… for practical purposes a working computer scientist just learns whatever math, law or science is needed to reach a goal. The odds that what is needed is something being taught in college are not very high, and get lower the more interesting the work is.
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It’s interesting how different sorts of math spark people’s brains in different ways. I absolutely loathed Algebra II and theoretical math sort of stuff, but geometry? Easy and fun, I could write out geometry proofs all day. Analysis? Sure, it’s not too tough, and kinda fun, too.
But when I got to college and was told I had one single math credit I had to fulfill, I chose a probability & statistics course, which sounded like it’d be along those lines. It was back to theoretical imaginary-number crap, and I struggled.
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You should take that up with the professional organizations that accredit CS programs.
I’ve taught in a couple of CS departments, including the introductory “Math for CS” course, and teaching it to students who have not had Calculus is a strange intellectual exercise, like writing a novel without using the letter ‘N’. You can do it, but it isn’t natural.
Calculus is a toolkit, the most powerful in Mathematics (and arguably all of Science); it gives students the power to solve, as an easy exercise, problems that great minds in earlier eras struggled with. It therefore makes sense to teach it to STEM majors even if they might end up in a career that doesn’t use it directly. Even if all a student remembers 20 years later is that there’s a relatively simple way to find an area or maximize a function without the answer being handed down by some deity, that’s useful; knowing that there are things you can actually know for reasons makes you wiser than, for example, Betsy DeVos.
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Any recommended way to do so? Texts? Online?
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There are a lot of college courses available on the net. I would suggest trying one - MIT had one available. Then enroll in a state or community college if you liked it. Part time.
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I didn’t really enjoy probability theory theory either. But I think with pretty much any maths you eventually run into something that is a slog to understand. When I was younger I hated that. Now it’s a bit like picking scabs. Concepts you don’t get but just can’t leave alone.
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