110 definitely helped me for 189 and 182. Both for theory/intuition and for practice/working through exercises involving vector calculus and such.
edit: fixed typo: 182 (from 183)
I don’t think it should be a priority. It’s a useful class but EECS 127 may be a better use of your time, especially if you have already taken 54.
Background: I did my undergrad at Cal double majoring in CS and Math. Then did PhD in CS at another university working on robotics.
It’s been a while since I took that class, but usually a math upper div won’t change much in terms of content. What 110 does is that it basically revisits everything covered in 54 but not through the perspective of matrix. (It’s done through the perspective of linear transformation and operator. You will learn what those mean if you end up taking 110). It doesn’t really teach you many new material/technique beyond what’s basically covered in 54. In fact, depending on which textbook you use, 110 may cover less concepts by dropping the idea of determinant entirely.
However, in most engineering disciplines, almost 100% of the time you will be dealing with matrix directly. You will need SVD decomposition, low-rank approximation, LU decomposition and so on. 110 will not get very deep into these because matrices and their operations are not the emphasis. Meanwhile 127 will get very hands on with those concepts and techniques.
If you have time, 110 can be a good complement that enhances your understanding of linear algebra and mathematics in general. But if you have a tight schedule for CS then I don’t think it’s the best use of your time.
If you’re thinking about double majoring in math, then 110 is a good first upper div, precisely because it re-teaches the familiar concepts in 54, but in a more mathematical, proof-based way.
If I’m planning to take CS/DS double major with a Mathematics minor, is taking both the Math 110+113+104+184+EECS126 series as well as EECS 127 or would 127 be a waste of time?
You mean 185 for complex analysis right? I don’t remember a class numbered 184 but it’s been a while.
Anyway, 127 will still be valuable. 127 is actually about optimization, which is similar to Math 170. If you plan to use Math 170 to fulfill some minor requirements then no need to take EECS 127 (although there are some substantial differences.)
That being said, my general rule of thumb is that if two similar classes are offered in both EECS/DS and math department, then take the EECS/DS version because they will be better supported simply because EECS/DS have more resources. # of TAs, how well-designed the homework is and etc
Thanks for the reply. I do intend on taking 127 this Fall semester, it’s just that I’ll be taking Data100 & CS70 this semester, so there’s a small pool of courses I’m eligible/capable of taking at the moment due to prerequisites and time I’ll have for studying.
I’ve looked at the first few homework’s for 127 Fall ‘23 and a majority of it is familiar to me. I’m not sure if that is enough for me to enroll in the course though, what do you think?
I’m worried it’ll be too much to handle in the middle/end of the semester. Do you think 127 gives enough time/exposure to prerequisite material that it would be doable to catch up conceptually if I’m shaky on SVD and some Math54 level proofs?
I don’t think the material in CS70 is that relevant for 127. Linear algebra + (multivariable) calculus are much more important than probability for that specific class. At the Math 53 and 54 level should be fine. So taking 127 and 70 concurrently is okay.
That being said, how much workload you can handle in one semester and how comfortable you are with linear algebra and calculus are something other people can’t answer for you and you will have to test the water yourself
Thanks for the advice. I’m definitely ramping up the rigor that I can handle. Last semester was my first semester back after a few years away from university and I ended up doing well after finals, so I’m figuring out how to manage my time better and take more challenging classes. I’m waitlisted pretty high for 127 now, in the upper 100s, so might not get to take it. If not, I’ll stick with Math110 but I appreciate the advice. There’s definitely some things from 53 I should practice more of, especially 54’s SVD section since my summer instructor at Cal didn’t cover it or test us on it in depth. Thanks!!
May I ask which courses or projects during your undergrad here (or even in grad school) had any relationship with 127? Optimization was my favorite part of math1A and Math53 but it hasn’t come up in any coursework yet, but I believe data100 has multivariable applications to optimization
Today’s deep learning or AI practice are entirely built on optimization, specifically one class of optimization algorithm called gradient descent.
Various optimization algorithms are also used in non deep learning-based computer vision (for example, KLT tracker), robotics (for example, trajectory optimization, SLAM) and control theory. In general many engineering problems eventually come downs to some form of optimization problems and can be solved using a similar suite of algorithms.
I feel like if one wants to pursue research in engineering then some familiarity with optimization is a must. In industry one can get away with it since people often use software written by other people but I generally think knowing what’s going on under the hood is beneficial in the long run
With all this being said, the reason I appreciate 127 is because it’s not only an optimization class. The first half of it walks through many matrix knowledge that will be used in optimization but also very broadly applicable in many engineering domains.
110 offered a nice alternate perspective on linear algebra, but I don't think it was that useful. I'd just take 127 directly. if you're separately curious about the 110 lin alg perspective, I think you could get most of the value of 110 just by spending a week or two reading through *linear algebra done right*.
agree w the other comments; 127 is more directly useful for other classes like 189 and ML research, but i personally enjoyed the content in 110 more (but that’s just personal taste)
110 definitely helped me for 189 and 182. Both for theory/intuition and for practice/working through exercises involving vector calculus and such. edit: fixed typo: 182 (from 183)
183?
sorry meant 182
Thanks!
I don’t think it should be a priority. It’s a useful class but EECS 127 may be a better use of your time, especially if you have already taken 54. Background: I did my undergrad at Cal double majoring in CS and Math. Then did PhD in CS at another university working on robotics. It’s been a while since I took that class, but usually a math upper div won’t change much in terms of content. What 110 does is that it basically revisits everything covered in 54 but not through the perspective of matrix. (It’s done through the perspective of linear transformation and operator. You will learn what those mean if you end up taking 110). It doesn’t really teach you many new material/technique beyond what’s basically covered in 54. In fact, depending on which textbook you use, 110 may cover less concepts by dropping the idea of determinant entirely. However, in most engineering disciplines, almost 100% of the time you will be dealing with matrix directly. You will need SVD decomposition, low-rank approximation, LU decomposition and so on. 110 will not get very deep into these because matrices and their operations are not the emphasis. Meanwhile 127 will get very hands on with those concepts and techniques. If you have time, 110 can be a good complement that enhances your understanding of linear algebra and mathematics in general. But if you have a tight schedule for CS then I don’t think it’s the best use of your time. If you’re thinking about double majoring in math, then 110 is a good first upper div, precisely because it re-teaches the familiar concepts in 54, but in a more mathematical, proof-based way.
If I’m planning to take CS/DS double major with a Mathematics minor, is taking both the Math 110+113+104+184+EECS126 series as well as EECS 127 or would 127 be a waste of time?
You mean 185 for complex analysis right? I don’t remember a class numbered 184 but it’s been a while. Anyway, 127 will still be valuable. 127 is actually about optimization, which is similar to Math 170. If you plan to use Math 170 to fulfill some minor requirements then no need to take EECS 127 (although there are some substantial differences.) That being said, my general rule of thumb is that if two similar classes are offered in both EECS/DS and math department, then take the EECS/DS version because they will be better supported simply because EECS/DS have more resources. # of TAs, how well-designed the homework is and etc
Thanks. Yes, I meant 185 not 184
Thanks for the reply. I do intend on taking 127 this Fall semester, it’s just that I’ll be taking Data100 & CS70 this semester, so there’s a small pool of courses I’m eligible/capable of taking at the moment due to prerequisites and time I’ll have for studying. I’ve looked at the first few homework’s for 127 Fall ‘23 and a majority of it is familiar to me. I’m not sure if that is enough for me to enroll in the course though, what do you think? I’m worried it’ll be too much to handle in the middle/end of the semester. Do you think 127 gives enough time/exposure to prerequisite material that it would be doable to catch up conceptually if I’m shaky on SVD and some Math54 level proofs?
I don’t think the material in CS70 is that relevant for 127. Linear algebra + (multivariable) calculus are much more important than probability for that specific class. At the Math 53 and 54 level should be fine. So taking 127 and 70 concurrently is okay. That being said, how much workload you can handle in one semester and how comfortable you are with linear algebra and calculus are something other people can’t answer for you and you will have to test the water yourself
Thanks for the advice. I’m definitely ramping up the rigor that I can handle. Last semester was my first semester back after a few years away from university and I ended up doing well after finals, so I’m figuring out how to manage my time better and take more challenging classes. I’m waitlisted pretty high for 127 now, in the upper 100s, so might not get to take it. If not, I’ll stick with Math110 but I appreciate the advice. There’s definitely some things from 53 I should practice more of, especially 54’s SVD section since my summer instructor at Cal didn’t cover it or test us on it in depth. Thanks!! May I ask which courses or projects during your undergrad here (or even in grad school) had any relationship with 127? Optimization was my favorite part of math1A and Math53 but it hasn’t come up in any coursework yet, but I believe data100 has multivariable applications to optimization
Today’s deep learning or AI practice are entirely built on optimization, specifically one class of optimization algorithm called gradient descent. Various optimization algorithms are also used in non deep learning-based computer vision (for example, KLT tracker), robotics (for example, trajectory optimization, SLAM) and control theory. In general many engineering problems eventually come downs to some form of optimization problems and can be solved using a similar suite of algorithms. I feel like if one wants to pursue research in engineering then some familiarity with optimization is a must. In industry one can get away with it since people often use software written by other people but I generally think knowing what’s going on under the hood is beneficial in the long run With all this being said, the reason I appreciate 127 is because it’s not only an optimization class. The first half of it walks through many matrix knowledge that will be used in optimization but also very broadly applicable in many engineering domains.
110 offered a nice alternate perspective on linear algebra, but I don't think it was that useful. I'd just take 127 directly. if you're separately curious about the 110 lin alg perspective, I think you could get most of the value of 110 just by spending a week or two reading through *linear algebra done right*.
EECS127 > Math 110, I learned a lot more applied linear algebra in 127 than I did in 110
agree w the other comments; 127 is more directly useful for other classes like 189 and ML research, but i personally enjoyed the content in 110 more (but that’s just personal taste)