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Can an undergrad manage 6 courses (1 grad) in a term?


ev a.

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Hello, I am an electrical engineering undergrad student who wishes to pursue graduate studies in CS, AI/ML and Computer Vision. I aim to take 2 EE, plus 4 CS courses. Algorithms, PL and Computer Vision for undergrad is set. I am considering a Pattern Recognition/Machine Learning course as an additional graduate course. All CS courses have no labs, yet some projects and surely homeworks.

 

Previously I have done this with my EE curriculum yet it was very tiring. In addition, I have to get best grades in these courses, hence additional burden may cause me failure at more than a single course.

 

By the way, there is an undergrad ML course but unfortunately not opened for fall term. This makes me think an undergrad vs grad course might have significant courseload difference. I consulted to the professor of the course, he said previously some undergrad students took it, and did well. Also, it requires good probability background, which I have from EE education.

 

Is this common (taking higher level courses) amongst CS undergrads? Is it managable for a good-enough student? Would you advise against it? Also, I can take a Parallel Programming course in place of this, which I believe will be useful in almost any area regarding CS, so would it be better/more appropriate for an undergraduate student? 

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This is a very personal decision that depends on your tolerance for "suffering". I'm from a different engineering discipline and I was in a BS/MS program so I had a few quarters were I was overloading with a split between undergrad and grad courses. However, I was the type of student who did better when I was under a lot of pressure but not every student excels under those conditions. That being said do you have an option to take the ML course in a different semester? If you want to get the highest grades possible, you may have to drop a course in order to learn the underlying principles to a sufficient level. Ask yourself whether you must take the course before you apply to grad programs or if you can work that into your SoP - that you are planning on taking the course in the spring. This way you can get high grades and work on your capstone design (I am assuming you're a rising senior and will be working on your capstone project this coming year). Good luck with your decision.

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This is a very personal decision that depends on your tolerance for "suffering". I'm from a different engineering discipline and I was in a BS/MS program so I had a few quarters were I was overloading with a split between undergrad and grad courses. However, I was the type of student who did better when I was under a lot of pressure but not every student excels under those conditions. That being said do you have an option to take the ML course in a different semester? If you want to get the highest grades possible, you may have to drop a course in order to learn the underlying principles to a sufficient level. Ask yourself whether you must take the course before you apply to grad programs or if you can work that into your SoP - that you are planning on taking the course in the spring. This way you can get high grades and work on your capstone design (I am assuming you're a rising senior and will be working on your capstone project this coming year). Good luck with your decision.

 

@eteshoe

Oh, I can suffer :) I don't have exactly that option, I can, but this is my final semester (upcoming fall) as an undergrad and I want to impress admission committees as much as possible, and since I will be working on ML area anyway, I assumed it wouldn't hurt to get a course on ML.

As for the dropping the course, It is not something I do quite often (honestly, never), mainly because after suffering for more than half of the semester (which usually is the amount of time to get comfortable with the subject at the minimum) I go ahead and finish the course.

 

And thanks for the answer, more experience and thoughts on course load is welcome. I learn quite a lot from the anecdotal experience.

Edited by ev a.
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