Is Calculus necessary for computer science student?

A software engineer probably does not need to study calculus, and it is less likely to be useful than graph theory, elementary logic, study of algorithms, etc. Of course, if you are implementing algorithms for use in science and engineering, calculus and numerical methods for approximating calculus operations will show up all of the time.

AI, on the other hand, is all about calculus (despite the best attempts of the machine learning community to "rebrand" concepts like numerical optimization, the chain rule, gradient descent, etc.) It's hard for me to imagine a successful data analyst or AI researcher who doesn't know at least the basics of calculus.

EDIT: In response to the answer suggesting you do not need calculus to be a data scientist at a company like Google, consider this blog post from a Googler with advice on the job search:

Math like linear algebra and calculus are more or less expected of anyone we’d hire as a data scientist

Calculus is a fundamental mathematical science - Learn it to broaden your mind and not necessarily to be graded at.it. It is fundamental for scientific computing. Programming in scientific filed specially engineering require background. I am surprised that you are studying engineering without calculus!!!

I’m a CS student myself so I can relate to what you’re asking. First of all, it really matters what branch of CS you’d like to pursue. For example, if you want to do cyber security(more specifically, cryptography), you will definitely need to know a lot of number theory. In your case, you’re interested in AI and data science but that’s still a bit vague; most people who’d like to do AI/data science, don’t really care about what’s going “under the hood”(which is not really that bad) and use libraries such as Pytorch, Tensor Flow, etc(but note that these people aren’t just AI enthusiastics; many of them work for big companies and are rather successful in their respective field). But there are people that are trying to make new, cutting-edge algorithms and write papers and in that case, you definitely will need more than just high school level math(university level calculus, linear algebra and statistics mostly). So if you are one of the former, high school level calculus, some university-level linear algebra and statistics(first year) would suffice. But if you’re one of the latter, you will need a lot more than just high school calculus and basic university linear algebra and statistics.

To sum it up, most people who do AI(again, not just enthusiastics; people who work for Google, Facebook, etc) do not always understand what’s going on in a library/module. The people who write these algorithms and papers do that. But if you have the time, try learning calculus, linear algebra and statistics so you’ll get a better understanding of what’s going on and maybe even you can make new algorithms that change the AI industry:)

EDIT

I think some people mistook what I said about some people not knowing how something works in AI: Does every successful data scientist know how regression works? Of course they do! How and why batch gradient descent works? 100%(you need calculus for these)! But do they all also know how restricted boltzman machine works? Probably not. Do they all understand VBEM? Of course not! The point is, I didn’t mean that people working for Google don’t know calculus or how an algorithm such as deep neural nets or NLP works; I just meant that you don’t need to be as good as most math students at calculus. Good luck!