Besides the mathematics, how hard is an engineering degree?

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SUMMARY

An engineering degree, particularly in Electrical Engineering (EE) or Mechanical Engineering (ME), presents significant challenges beyond mathematics, especially when aiming for a GPA of 3.5 or higher. Students often face a rigorous course load, typically comprising five demanding classes simultaneously, which can include complex subjects like linear algebra, probability, and differential equations. While foundational mathematics is crucial, the application of these principles in real-world scenarios is emphasized, and many students find that not all mathematical concepts are directly tested. Ultimately, success in engineering hinges on managing coursework effectively and understanding the practical applications of mathematical theories.

PREREQUISITES
  • Understanding of Differential Equations
  • Familiarity with Linear Algebra
  • Knowledge of Probability and Stochastic Processes
  • Basic concepts in Signals and Systems
NEXT STEPS
  • Research advanced topics in Linear Algebra for engineering applications
  • Explore machine learning techniques that utilize Probability and Stochastic Processes
  • Study the principles of Signals and Systems in depth
  • Learn about the applications of Differential Equations in engineering contexts
USEFUL FOR

Students considering an engineering degree, particularly those interested in Electrical or Mechanical Engineering, as well as current engineering students seeking to understand the academic challenges and expectations of their programs.

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I have read countless articles, threads, discussions, you name it, about engineering, because I have always been back on forth on whether I will succeed at it or not. I have been going to a state university for two years, and am starting at the technical institute this summer. Deciding between EE and ME. Please stick to either 1) answering the following question or 2) providing an insight on the choice between EE and ME that people don't say in every other thread. That being said, my question:

How hard is an engineering degree, whether EE, ME, or others in general, once you get past the mathematical aspect?
I have already taken through Differential Equations, with all A's. So, as far as I am aware, it is all applications of those principles now.

If it will help, I have been attending GSU and am going to Georgia Tech
 
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It is hard, but manageable. Think of the sheer number of students who get engineering degrees every year.

A better question is, how hard is it to get a GPA of, say, 3.5 in your engineering degree?

One could technically get a C in every class, graduate, then still find an engineering job with an employer that doesn't care about GPA.

However, if getting a high GPA is very important to you, then an engineering degree may be very hard indeed.
 
The hardest part about engineering is that they don't teach you enough mathematics before you start. But all the professors know it, and you aren't exactly being tested on the raw math anyway. So it doesn't turn out to be that bad. A personal example (EE over here) was when I took pattern recognition. There were many mathematical concepts from linear algebra presented in the book that till this moment I don't understand. But of course the test was primarily things I and my fellow engineers could understand. I remember pragmatically skipping entire sections of the book: "This will not be on the test." (and "I couldn't understand this even if I wanted to at this moment. I really need to take a linear algebra class first").

On a side note, as you become a more influential engineer, you will begin to take courses from the math department as well as study on your own. Eventually, it will all make sense if you want it to make sense.

As for EE, there are 3 primary mathematical fields that I have experienced in my coursework:
Linear algebra -- It is used a lot in representing and maneuvering data through algorithms. So it is often seen in signals & systems(e.g. an image can be a matrix of data applied to a system), controls (your state space are matrices, inputs, outputs, etc.), pattern recognition (your features to classify/training samples/ etc. are all matrices), machine learning, etc.

Probability/stochastic processes -- This is used of course a lot in machine learning/ pattern recognition/communication/signals&systems (when applied to random signals) etc.

differential equations -- LTI LTI LTI, everything in controls/signals/systems is a linear, time-invariant system so far. These are all nth order differential equations analyzed via numerous transforms and techniques.
 
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I find the difficulty with engineering isn't really one class but that you are taking 5 difficult classes at the same time. Most schools that I have looked into don't require very many fluff classes. So you are going to be taking 5 engineering/science/math classes at the same time.
 
In my experience, those EE kids know a lot of math. Complex analysis, Fourier stuff, PDE's, Linear algebra, and even some set theory. I wouldn't bet on your math knowledge stopping at differential equations.
 

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