#### quantsmodelsbottles

##### Active Member

Hi all,

In looking at GPA cutoffs for both grad school programs and job applications, I see it as imperative to make up for my CS GPA, which is ridiculously low (mostlys Cs and a few Bs). While my math/major GPA is high (but not even that high, hovering around 3.5), the CS GPA will be a huge bottleneck, especially if applying for machine learning focused CS grad programs, to the point where I can expect auto rejections. What are some good accredited online courses for CS? Discrete Math is actually one of the math classes I did poorly in and it is CS related, so it will probably bring my math gpa solidly above 3.5 as well. Where are some good sources to retake and how much will retaking help?

There's no good way to explain why it is so low to anyone in charge of hiring/admissions. The real reason it is so low is that the CS curriculum at my school was very software development and compiler/operating systems focused, not quantitative at all. And what I was really interested in was quantitative topics like programming logic, algorithm design, and ML/DL, so I had zero interest. Same for the "applied" math curriculum really, just a lot of watered down plug and chug. I had to pick up the slack on my own and take online stats courses and work on interview prep books to get up to speed.

In looking at GPA cutoffs for both grad school programs and job applications, I see it as imperative to make up for my CS GPA, which is ridiculously low (mostlys Cs and a few Bs). While my math/major GPA is high (but not even that high, hovering around 3.5), the CS GPA will be a huge bottleneck, especially if applying for machine learning focused CS grad programs, to the point where I can expect auto rejections. What are some good accredited online courses for CS? Discrete Math is actually one of the math classes I did poorly in and it is CS related, so it will probably bring my math gpa solidly above 3.5 as well. Where are some good sources to retake and how much will retaking help?

There's no good way to explain why it is so low to anyone in charge of hiring/admissions. The real reason it is so low is that the CS curriculum at my school was very software development and compiler/operating systems focused, not quantitative at all. And what I was really interested in was quantitative topics like programming logic, algorithm design, and ML/DL, so I had zero interest. Same for the "applied" math curriculum really, just a lot of watered down plug and chug. I had to pick up the slack on my own and take online stats courses and work on interview prep books to get up to speed.

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