Functional analysis and real analysis

AI Thread Summary
Taking real analysis before functional analysis is debated, with many programs assuming prior knowledge of real analysis, while others only require an introductory course. The necessity of functional analysis for careers in computational science, simulation, and mathematical modeling is questioned, as both subjects are seen as abstract and proof-driven, potentially diverting focus from more practical courses like programming, advanced linear algebra, and numerical analysis. Experiences shared indicate that functional analysis may not be directly applicable in many applied math fields, with some professionals in physics not having taken such courses. The consensus suggests prioritizing practical skills over pure mathematics unless one has a strong inclination for proof-based math and can manage the workload without compromising other studies.
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In my schools functional analysis course, under prerequisites, it says "real analysis would be a good preparatory course, but is not required". In the concurrent real analysis thread, it was mentioned that real analysis is a stepping stone to functional analysis.

I'm curious about two things:

1) how essential is taking real analysis prior to functional analysis?
2) how essential is functional analysis to someone interested in computational science, simulation and general mathematical modeling (including statistic/stochastic modelling)?

Until now, I've assumed both courses to be no-brainers for people interested in a career in applied math, but if both real and functional analysis are abstract and proof driven, bordering on "pure math", maybe ones focus should be elsewhere.

Given infinite time, I'd be happy to take both courses. But if they're competing with programming courses, advanced linear algebra/numerical analysis, fluid dynamics, quantum mechanics etc, are they really worth it?
 
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You need to discuss this with your math adviser - it depends on the details of each course as taught.

In many programs functional analysis assumes that you have had the senior level real analysis - in other programs they may only require an "introduction to real analysis".

More linear algebra is always good for physics! And today everybody needs to know programming - and for physics a course in numerical analysis is more useful than real analysis.
 
I took this class and it was one of the biggest mistakes I made,

It was kind of interesting, but I have never used ANYTHING besides the definition of Hilbert spaces and metrics and stuff like that ever again. More importantly, while I was taking the class I complained about it to a bunch of physics academics and none of them had taken this kind of class before, if they ever had to use it they just learned what they needed, which is what I would have preferred.

In my opinion this subject isn't something you can quickly learn in one semester while juggling several other classes, it's something that requires A LOT of time and basically, unless you're a genius, it requires you do a lot of example questions to grasp the concepts.

I'm not really sure why or where it is used in programming, but I am not an experienced programmer. Where I'm from the only degree's that suggest real and functional analysis are actuarial studies, statistics and mathematics.

If I were you I'd pick a programming course or like UltrafastPED said, the algebra class.

I hope I haven't replied too late.
 
Both subjects are pure mathematics, and almost completely useless to you. You're better off simply picking up useful tidbits on the go than risking your GPA and wasting your time.

Now, if you are extremely talented and enjoy proof based pure mathematics, and do not think either course will pose a threat to your grades/research/whatever other important things you're up to, by all means try it.
 
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