Is it just the linear algebra you're struggling with? Because that's really only 10-15% of CSE 6040, basicaly the numpy sections. The rest is just python and learning how to use the language and its relevant libraries (pandas and numpy).
I took CSE 6040 before ISYE 6501 and even though I didn't have the background for some of the things we were doing (e.g., implementing PCA in python without understanding what PCA actually was), I still had very few problems with the course and found it relatively easy because I'm generally comfortable with python. Admittedly, I have familiarity with linear algebra from my undergrad years, so while I also found the numpy sections harder, I could still understand what's going on once I saw the solution and it easily 'clicked'.
If python/programming is your problem in general, then that's not necessarily good news because there's a lot of it in the program. But if you found ISYE 6501 easy, that also has a good amount of coding so I don't know...
If not understanding the concepts behind the programming is an issue, remember that CSE 6040's focus is more on building your programming proficiency than with teaching you the mathematical concepts (like I said, I implemented PCA with ease without understand what it actually meant).
If the linear algebra alone is the problem, then...mixed news for you. There are some courses, like Deterministic Optimisation, High Dimensional Data Analytics, Computational Data Analytics, which all require linear algebra knowledge as a prerequisite. There are probably a few others I haven't mentioned. You'd struggle with these. On the other hand, none of these are really compulsory (ISYE 6740 CDA is, but only if you're taking the computational analytics track) so you can avoid them and take courses without significant knowledge of linear algebra if you want, though linear algebra really does form the foundation of a lot of data science because of its ability to quickly process information without running full-blown for loops so you'll likely encounter it again in different places.
It's just knowledge like any other, though. I've found that linear algebra is often taught in an obtuse manner, where the focus is more on the mechanical operations than the actual intuition and meaning behind those operations (e.g., how to find the inverse of a matrix instead of what the inverse means and why you'd want to use it in solving real problems). I've found that once you understand that intuition, linear algebra is generally kinda easy, but if it's not taught properly and all you learn is those mechanical operations and how to do them, you can easily start getting headaches.
But there are good courses that can help you get up to speed. Some of these are:
I'd recommend taking them in that order. The 3blue1brown videos will give you the intuition for what different LA operations are all about and the Coursera specialisation will reinforce this and teach how to compute (and program) them. Then, go back to the 3blue1brown videos to reinforce that intuition of what all those mechanical operations you learned to perform are actually useful for. If you do just these two, you should have at least a good foundation for OMSA. You can refer to the textbook if you want as well to build out your knowledge more formally.
If you want to learn even more/with more academic rigour, the LAFF courses have an excellent reputation and there are three follow-on courses for even more advanced linear algebra if you want to do that. Alternatively, you can also follow the MIT lectures. Gilbert Strang is the author of one of the most popular LA textbooks out there, so you know you're in good hands.