But career-wise, it's a mediocre choice in most Western countries. (Possible exception is Germany, where engineers have a similar status to doctors and lawyers.)
Most people have no clue what EE even is, or just how much math and engineering goes into building everyday devices and services.
(A friend of the family said "Great! You'll be able to get a job repairing TVs!" when I got my course offer.)
Here's the thing, though: PDEs are NP-hard. There isn't a generalizable way to model dynamics. On the other hand, dynamics come up everywhere:
- How is the pandemic going to evolve?
- How will incentive structures skew cultures?
- How do I build a suspension for my car?
- How does heat leak from my house?
- How does my understanding evolve with learning?
... and so on.
What EE does -- and I think uniquely -- is given intuitive, graphical tools to think about differential equations, in tools like Laplace, Body, Nyquist, root-locus, and so on.
They also give a lot of applied experience in applying those, including in contexts with nonlinearities. An op amp will clip on both sides, which you model as a linear differential equation (which is easy enough to reason about) and a memoryless, time-invariant nonlinearity. You squint. You kinda ask yourself how it would work if it /were/ linear, and the nonlinearity just cut gain. And at some point, after doing it enough, you have intuition for what it will do.
With the EE-specific stuff, I can intuitively reason about these things think through to design.
EE is all about modeling -- building simpler equations which approximate more complex ones in ways which give intuition -- so this is also usually correct or almost correct. Indeed, if you go onto grad level courses in control theory, you'll see formalizations of this intuition, where for example, a time-variant system or a nonlinear system is modeled as a linear time-invariant system, together with a bounded error.
A lot of the mathy stuff -- which I've learned a fair bit of as well -- is in abstract more general, but in practice, gives much less intuition.
My experience with the real world is that there are rarely actual differential equations handed to me. I kinda get that we've set up some pricing structure, or some incentive design, or whatnot, but I can't model it formally. I know which way things push, and whether those integrate or not. I can draw a block diagram and reason about how it will behave, in a way the math side doesn't let me do.
Errr, no they don't. In terms of pay and status Doctors and Lawyers trump Engineers every day of the week in Germany, the only exception being the engineers with PhDs who are tech leads in some well known research institute or big-brand company like Audi or Porsche.
Not once did I use Laplace in EE. It was all cheat sheets or applying data sheets and doing some adhoc calculations in excel or taking a wild guess and iterating.
After twenty years of doing IT related stuff I’ve forgotten how to even differentiate stuff.
1. I did learn them well, and so I did use Laplace quite often in EE.
2. I jumped careers not into IT, but into tracks which leveraged both programming and a mathematical skill set.
I'll mention: I'd be bored out of my wits doing just IT. The intersection of IT and math includes computer graphics, visualizations, robotics, machine learning, fintech, image processing, and a ton of other stuff I find much more fun and fulfilling.
That's not an implicit commentary on your path, by the way, just an explanation of mine. We all have different goals, desires, values, constraints, etc.
I sought areas where I could learn more math and use it to stand out from the crowd, albeit to mixed results, because if your manager can’t read your analysis paper he may not be impressed either, and sometimes the reverse.
If you know a little bit of math, there's no benefit.
If you know enough math to jump to e.g. medical imaging, robotics, controls, simulators, image processing, ML, or similar, there's a ton of benefit.
An EE degree ought to give enough background to get there, although it may involve a year or two of study in a particular domain, and a side project to prove you have the skills.
* Circuits are physical implementations of differential equations, and EE gives a unique way to intuitively think about dynamics, which applies to finance, epidemiology, and just a really diverse range of domains.
* With a rigorous EE background, you can rapidly pick up most domains of engineering (think Elon Musk), since you've got all the mathematical foundations. The reverse isn't true. The way math is taught in EE is broader than e.g. mechanical, civil, or other engineering disciplines, where it tends to be more domain-specific. EE gives you a lot of depth in probability, error analysis, signal processing, controls, calculus, linear algebra, etc. I think the only things missing are statistics and discrete math, and I picked those up elsewhere.
High-performance board-level EE is insanely fun. Incredibly creative. You get to build stuff, design stuff, do math, and it's just a huge diversity of intellectually-fulfilling stuff.
IC design is a bit less fun, due to the many-month turn cycles (develop, wait months and hundreds of thousands dollars, and test/debug), but not bad.
However, the EE industry sucks:
- Pay is not bad, but much worse than other jobs you can get with an EE degree.
- Work culture has all the worst excesses of the eighties -- think of Office Space style cubicle farms, dress codes, conservative management, ISO processes, and paperwork.
- Yet it's somehow adopted some of the worst excesses of the 2010s; it no longer feels like work is a family or a community
- And it's hard to get into. There are virtually no jobs for junior-level EEs (which isn't just BSes -- in the Great Recession, I knew bright newly-minted Stanford/MIT/Caltech/etc. Ph.Ds who couldn't find jobs).
- Even at the senior-level, there's a bit too much of a boom-and-bust cycle, without the booms ever getting that boomy, but the busts being pretty busty.
I spent maybe five years doing EE work after my EE degree, and I think that was enough. I've been out for a long time now. I still do EE as a hobby, and I enjoy it, but the industry culture isn't one I remember with fondness.
I suspect a lot of this stuff will continue to disappear from the US into Asia; that transition is rapidly in progress. US firms maintain specialized knowledge in some areas (e.g. particular types of MEMS devices), but there are plenty of places we've fallen behind. I don't see us on the path to regain leadership. I think some of this is cyclical. Declining industries don't make for good employers, and poor employers don't make for growth industries.