<p>Now I know engineering math is really doing that traditional application of calculus, etc. to real life problems and making things work. What about computer science? How do CS majors use math in their work? Like software engineers, game developers, IT, or cybersecurity? Is math for CS majors more so like a core or primary material that everyone has to learn, but is not really applied in their work?</p>
<p>oh and I’m asking about CS majors in industry. not academia…
thanks</p>
<p>You have CS research areas like Computer Vision that focuses on extracting data from images. As far as the pattern-recognition piece of computer vision, Graph Theory (part of discrete mathematics) is used heavily. Linear Algebra is also used in Computer Vision.</p>
<p>Computer simulation of wavelets uses a ton of linear algebra.</p>
<p>Optimization computer networks of course uses graph theory.</p>
<p>A branch of linear algebra called Markov Chains is used in its computational state in order to simulate the measuring of the performance of computer networks.</p>
<p>oh, but what about just industry? Like databases or security? I’ve read that CS has a lot of theory behind it. Is the theory in undergrad just intro courses that are built upon in grad school or is it just background knowledge for just CS majors not planning on going to grad school for CS?</p>
<p>As far as security, Cryptology is a course which is usually a cross-listed course: meaning that it is offered jointly by the math and computer science departments.</p>
<p>As far as databases, you can definitely apply mathematical techniques such as Queuing Theory and more statistical techniques like Experimental Design to databases. </p>
<p>For example, lets say a data warehouse receives millions of small files that need to be parsed, transformed a loaded to the database tables. You could use the processing time as the service time and the waiting time for file not yet processed and compute all of the other metrics from Queuing Theory.</p>
<p>Another example: In theory, you can have the set of all possible performance tuning options of Oracle or SQL Server and apply Experimental Design (or Analysis of Variance) techniques to produce the optimal settings for the database performance.</p>
<p>oh I see thanks. even though I have absolutely no idea what the math stuff you just mentioned are about haha.</p>