What CompE/statistics skills should EE undergrads have?

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In summary, the conversation discusses the skills that would be useful in a CSE/EE program after graduation. Some potential topics include data structures and algorithms, statistics (especially for semiconductors), and computer architecture, FPGAs, or machine learning (for robotics). The conversation also touches on the importance of statistics in signal processing and quantum mechanics for solid-state physics and chemistry. It is noted that many of these skills are covered in relevant courses, but there is also room to take electives outside of the department to further explore these areas.
  • #1
24karatbear
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Hello,

I apologize for the ambiguous thread title. I am in the process of choosing electives and was wondering what sort of CSE/statistics skills (outside of what is required in a typical EE program) would prove useful to me after I graduate. Aside from core requirements, I have completed introductory programming courses (C++, MATLAB). Some topics I've been looking into:

- Computer Science and Engineering: Data structures and algorithms

- Statistics: My school requires all EE's to take a probabilistic analysis class with the following description: "Probabilistic and statistical analysis of electrical and computer systems. Discrete and continuous random variables, expectation and moments. Transformation of random variables. Joint and conditional densities. Limit theorems and statistics. Noise models, system reliability and testing." Would taking additional statistics courses be useful?If it helps, some of my interests lie in astronautics, semiconductors, and robotics.

Does anyone have any suggestions?
 
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  • #2
24karatbear said:
If it helps, some of my interests lie in astronautics, semiconductors, and robotics.

that is a very broad range of topics...
statistics would be useful for semiconductors

anything with computer architecture, fpgas, or machine learning would be good for robotics
 
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  • #3
donpacino said:
that is a very broad range of topics...
statistics would be useful for semiconductors

anything with computer architecture, fpgas, or machine learning would be good for robotics

Hey, thank you!

Yeah, I haven't really narrowed down my interests yet, so everything is still a bit broad as I try to discover what I really want to do after I graduate. Your suggestions help a lot, though.
 
  • #4
If you're interested in signal processing, you absolutely will need statistics. Semiconductors and anything solid-state physics related will involve quantum mechanics, and statistics in QM, depending on the course, can be anywhere from useful to downright necessary. Also necessary if you might want to take any chemistry or thermodynamics-related options (if they're offered).

My experience, though, has been that the statistics skills are covered in the relevant courses as necessary.
 
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  • #5
jack476 said:
If you're interested in signal processing, you absolutely will need statistics. Semiconductors and anything solid-state physics related will involve quantum mechanics, and statistics in QM, depending on the course, can be anywhere from useful to downright necessary. Also necessary if you might want to take any chemistry or thermodynamics-related options (if they're offered).

My experience, though, has been that the statistics skills are covered in the relevant courses as necessary.

Thank you so much for responding!

I just did a quick search on my school's course catalog I found that some of the statistics skills are actually covered in our required courses like you said. I do have space to take electives outside of my department so I think I will look into some QM physics classes too. I'll keep that information in mind about signal processing. Appreciate your help!
 

What are the most essential CompE/statistics skills for EE undergrads?

The most essential CompE/statistics skills for EE undergrads include proficiency in programming languages such as C++, Java, and Python, understanding of probability and statistics concepts, data analysis and visualization skills, and knowledge of machine learning algorithms.

Why are these skills important for EE undergrads?

These skills are important for EE undergrads because they are increasingly used in various fields of engineering, including electrical and computer engineering. With the rise of big data and artificial intelligence, having a strong foundation in programming and statistics enables EE undergrads to adapt to the changing landscape and stay competitive in their field.

How can EE undergrads develop these skills?

EE undergrads can develop these skills by taking relevant courses in their curriculum, participating in hands-on projects and internships, and practicing on their own through online resources and coding challenges. They can also attend workshops and seminars to learn about the latest developments in these areas.

Which industries or job roles require these skills?

Industries such as telecommunications, robotics, data analytics, and software development require these skills from EE undergrads. Job roles that may require these skills include data analyst, software engineer, systems engineer, and research scientist.

How can having these skills benefit EE undergrads in their career?

Having these skills can benefit EE undergrads in their career by making them more versatile and marketable to potential employers. They can also open up opportunities for higher-paying jobs and career growth in emerging fields such as data science and artificial intelligence.

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