Do you really think you can talk down to me? Good try, no cigar.

It's not just dentists, although it certainly is a complete waste of time for dentists to study calculus.

It's fairy well known that the typical college math curriculum hierarchy is not useful for many people, regardless of their occupation. The reason we teach college math the way we do is based on antiquated thinking and tradition. It's not based on any use case encountered in the real world.

Quora:

Are college calculus courses useless for most engineers?

Arteom Korotchenya

Arteom Korotchenya, specialist degree Civil and Structural Engineering

Updated Sep 19 2018

It is useless. No one in their clear mind would solve indefinite integrals or differential equations manually, or try to use combinatoric definition of a determinant to find eigenvalues when dealing with stability of structures problems.

In theory, calculus course is a prerequisite for engineering courses - which i as a trained structural engineer took - such as vector mechanics, strength of materials, structural analysis and finite element analysis.

These are important courses, but for the ideal engineer. In mundane structural engineering there are abundance of finite element method programs, which take 3D model of the, for example, office building and produce quite reliable output. Ideally, the user should know the basics of finite element analysis, but really, what to check in program such as ETABS? Mesher? Solver? Well, the truth is that many computer programs have at last one common solver library. Would a human being solve a system of 300 000 linear equations by hand? Not likely. There are alternative and faster ways of checking the validity of results which don’t require calculus skills, and when they nevertheless do - for example dynamics problem - , there are “wolfram mathematica” and “matlab” at one’s service.

I can even say that calculus is useless to an engineer who wants to become a professor. To achieve a true understanding of a theory behind engineering methods one need an advance mathematical courses up to functional analysis, topology and elements of tensor calculus.

Before computers calculus could have been a valuable skill, but nowadays most real world engineers are in fact more sort of technicians who possess some intuitive understanding of various disciplines but mostly CAD monkeys.

One could say that it is bad, but the truth is that it is the benefit of a progress. CAD monkeys are cheap, houses and airplanes are getting cheaper, cad monkey could allow themseves to buy more for earned money.

Software engineering industry because of it’s relatively young age resist the progress and keeps clinging at the illusion that good software engineer is the one who can restore the details of how a computer creates random numbers or write an advanced sorting algorithm or who can take an indefinite integral in five minitues. However, as it was previously mentioned, the average developer of Finite element Analysis program don’t write Kholetsky algorithm from scratch. An average game designer uses ready engine, though occasionaly he would need to remember something from lilear algebra.

To sum up. Powerful computers created a division in the engineering profession. At the one hand there are CAD monkeys, who used to have structural analysis, theoretical mechanics and four semesters of calculus, but don’t use that in their daily work. At the other hand there are professors and R&D engineers whom i endlessly admire and who are busy in creating new powerful algorithms, new processors and who know the necessary mathematics behind their work. But that mathematics have nothing to do with calculus in form of bag of tricks aimed at taking integrals, solving differential equations, taking Lagrangians or finding limits of a function.

Upd.

When i had my theory of elasticity class, we had to find fourth derivative of a polynomial of - probably forth order - with rather ugly coeficients. I took the first derivative and then feed the polynomial to Mathematica, not feeling sorry for that, cause i didn’t understand how procedural manipulation on which i would have spent half an hour would have enriched my knowledge.

When i took advanced undergraduate microeconomics course, we students were expected to take Lagrangians to solve max(mini)misation problem. The strategy to solve the problem was presented as the above mentioned bag of tricks: find partial derivatives, and so on. It was not clear why the procedure is true. I thought to use minimise function of Mathematica but the professor wouldn’t have accept the solution, hence I limited myself to using “grad” function in mathematica and that at least forced me to think about the answer obtained. Clear picture, why the procedure was true came after exercises from V. Zorich Analysis book.

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Calculus Is So Last Century

Training in statistics, linear algebra and algorithmic thinking is more relevant for today’s educated workforce.

By Tianhui Michael Li and Allison Bishop

March 4, 2016 6:09 pm ET

Can you remember the last time you did calculus? Unless you are a researcher or engineer, chances are good it was in a high-school or college class you’d rather forget. For most Americans, solving a calculus problem is not a skill they need to perform well at work.

This is not to say that America’s workforce doesn’t need advanced mathematics—quite the opposite. An extensive 2011 McKinsey Global Institute study found that by 2018 the U.S will face a 1.5 million worker shortfall in analysts and managers who have the mathematical training necessary to deal with analysis of “large data sets,” the bread and butter of the big-data revolution.

The question is not whether advanced mathematics is needed but rather what kind of advanced mathematics. Calculus is the handmaiden of physics; it was invented by Newton to explain planetary and projectile motion. While its place at the core of math education may have made sense for Cold War adversaries engaged in a missile and space race, Minute-Man and Apollo no longer occupy the same prominent role in national security and continued prosperity that they once did.

The future of 21st-century America lies in fields like biotechnology and information technology, and these fields require very different math—the kinds designed to handle the vast amounts of data we generate each day. Each individual’s genome contains more than three billion base pairs and a quarter of a million genomes are sequenced every year. In Silicon Valley, computers store over 100 GBs of data—more information than contained in the ancient library at Alexandria—for every man, woman and child on the planet.

Accompanying the proliferation of new data is noise, and a major job for data analysts and scientists is to tease out true signal from coincidence and noise. Knowing when a result is due to chance versus when it is statistically significant requires a firm grasp of probability and statistics and an advanced understanding of mathematics.

We no longer think of outcomes as being triggered by a single factor but multiple ones—possibly thousands. To understand these large and complex data sets, we need an educated workforce that is also equipped with a firm understanding of multivariate mathematics and linear algebra.

Computers and computation are ubiquitous and everyone—not just software engineers—needs to learn how to think algorithmically. Yet the typical calculus curriculum’s emphasis on differentiation and integration rules leaves U.S. students ill-equipped at posing the questions that lead to innovations in computation. Instead, it leaves them well-equipped at performing rote computations that can be easily done by a computer.

We’re not saying calculus shouldn’t be taught. Calculus, like any rigorous technical discipline, is great mental training. We would love for everyone to take it. But the singular drive toward calculus in high school and college displaces other topics more important for today’s economy and society. Statistics, linear algebra and algorithmic thinking are not just useful for data scientists in Silicon Valley or researchers for the Human Genome Project. They are becoming vital to the way we think about manufacturing, finance, public health, politics and even journalism.