Course reviews
2025-12-??
Since last semester I've been writing course reviews after each batch of finals is over, and now that I have a blog, I can make them longer! This will be a little bit stream of consciousness, apologies in advance. At least you can tell I didn't write this with AI.
2025-12-??
Since last semester I've been writing course reviews after each batch of finals is over, and now that I have a blog, I can make them longer! This will be a little bit stream of consciousness, apologies in advance. At least you can tell I didn't write this with AI.
MAT301 / Groups and Symmetry / Prof. Benjamin Gammage
Poor Prof. Gammage. In his first semester at UofT (from Harvard), he was way too nice to us by UofT math standards, everyone knew it, and took advantage of him anyway by telling him they were disappointed in their performance on the midterm. The midterm average was in the 80s. And it was a tiny portion of our grade, along with weekly assignments (three of which we could drop). But Prof. Gammage felt terrible and promised that if we did better on the final, our mark on the final would be worth an extra 30% to replace the midterm. There were three questions on that midterm, all easier than the homework. If people did badly on it it was their own fault. (but they didn't, because the average was in the 80s!!!)
I liked Prof. Gammage, though. My introduction to him was his personal website, where he has a picture of himself pointing to a grave with his last name on it. He came to class every day in sandals-- the only time I saw him in closed toe shoes was during the final, when it was snowing. But week 12? Sandals. Also fun wide brimmed hats and floral button-down shirts. Generally probably the best dressed person in the math department. In week 2, someone had to tell him that we typically get a break halfway through a two-hour lecture, and he encouraged us to "shake our sillies out". Definitely the guy you want teaching your 9am lecture.
Our textbook was (apparently) the industry standard, Contemporary Abstract Algebra. Prof. Gammage hardly used any of the same notation as the textbook, so it was a learning curve for both us and the TAs, who were following the textbook religiously in tutorial. I had trouble with the -morphisms and didn't really understand why we had a whole detour between isomorphisms and homomorphisms (and why the textbook introduced isomorphisms before homomorphisms??????), but other than that, I thought the textbook was pretty good. I appreciated all the practice problems, but the answers were pretty useless, giving no explanation for anything. Assignments and the midterm were designed to check that we'd been paying attention in lecture rather than trip us up, a foreign concept at UofT. That's the Harvard influence I guess, but I'm not complaining. I also had multiple friends in the course, so we studied and checked over our assignments together.
Studying for the final, I was mostly concerned about remembering all the theorems. I mean, it's really all just Lagrange's theorem and maybe also the (unfortunately abbreviated) Fundamental Theorem of Finite Abelian Groups, but there are all sorts of corollaries to remember and I knew I wouldn't exactly have time to derive everything I needed. I've heard professional mathematicians say they enjoy their subject because it doesn't require memorization, but for a three-hour exam, I don't know how I could have gotten by without a little memorization. The final was harder than the midterm, but doable. I finished early, which is always a good sign.
Poor Prof. Gammage. In his first semester at UofT (from Harvard), he was way too nice to us by UofT math standards, everyone knew it, and took advantage of him anyway by telling him they were disappointed in their performance on the midterm. The midterm average was in the 80s. And it was a tiny portion of our grade, along with weekly assignments (three of which we could drop). But Prof. Gammage felt terrible and promised that if we did better on the final, our mark on the final would be worth an extra 30% to replace the midterm. There were three questions on that midterm, all easier than the homework. If people did badly on it it was their own fault. (but they didn't, because the average was in the 80s!!!)
I liked Prof. Gammage, though. My introduction to him was his personal website, where he has a picture of himself pointing to a grave with his last name on it. He came to class every day in sandals-- the only time I saw him in closed toe shoes was during the final, when it was snowing. But week 12? Sandals. Also fun wide brimmed hats and floral button-down shirts. Generally probably the best dressed person in the math department. In week 2, someone had to tell him that we typically get a break halfway through a two-hour lecture, and he encouraged us to "shake our sillies out". Definitely the guy you want teaching your 9am lecture.
Our textbook was (apparently) the industry standard, Contemporary Abstract Algebra. Prof. Gammage hardly used any of the same notation as the textbook, so it was a learning curve for both us and the TAs, who were following the textbook religiously in tutorial. I had trouble with the -morphisms and didn't really understand why we had a whole detour between isomorphisms and homomorphisms (and why the textbook introduced isomorphisms before homomorphisms??????), but other than that, I thought the textbook was pretty good. I appreciated all the practice problems, but the answers were pretty useless, giving no explanation for anything. Assignments and the midterm were designed to check that we'd been paying attention in lecture rather than trip us up, a foreign concept at UofT. That's the Harvard influence I guess, but I'm not complaining. I also had multiple friends in the course, so we studied and checked over our assignments together.
Studying for the final, I was mostly concerned about remembering all the theorems. I mean, it's really all just Lagrange's theorem and maybe also the (unfortunately abbreviated) Fundamental Theorem of Finite Abelian Groups, but there are all sorts of corollaries to remember and I knew I wouldn't exactly have time to derive everything I needed. I've heard professional mathematicians say they enjoy their subject because it doesn't require memorization, but for a three-hour exam, I don't know how I could have gotten by without a little memorization. The final was harder than the midterm, but doable. I finished early, which is always a good sign.
MAT332 / Introduction to Graph Theory / Prof. Hunter Spink
The title "Introduction to Graph Theory" implies it's the first in a series of multiple graph theory courses, but other than APM461 (which I'm planning to take next year) I don't think it is. *trump voice* Very Sad! Now I have to do the next two semesters with no graph theory. I knew this would be a banger course when Prof. Spink walked in wearing a San Francisco Giants hat, and I was right. Especially at the beginning of the course, all of the material felt very motivated and like it had a clear progression, unlike some courses this semester (looking at you, MAT344). I also appreciated that we didn't end with (what was in my opinion) the hardest material, but instead wound down with Ramsay theory. Love Ramsay theory. I made this meme and snuck it into my volunteer notetaker notes, and Prof. Spink either didn't notice or didn't care when he uploaded the notes to the Quercus.
The title "Introduction to Graph Theory" implies it's the first in a series of multiple graph theory courses, but other than APM461 (which I'm planning to take next year) I don't think it is. *trump voice* Very Sad! Now I have to do the next two semesters with no graph theory. I knew this would be a banger course when Prof. Spink walked in wearing a San Francisco Giants hat, and I was right. Especially at the beginning of the course, all of the material felt very motivated and like it had a clear progression, unlike some courses this semester (looking at you, MAT344). I also appreciated that we didn't end with (what was in my opinion) the hardest material, but instead wound down with Ramsay theory. Love Ramsay theory. I made this meme and snuck it into my volunteer notetaker notes, and Prof. Spink either didn't notice or didn't care when he uploaded the notes to the Quercus.
Also one about trees (right).
Lecture was always a wild ride. Part of this was Prof. Spink himself, who would say things such as:
(about Eulerian trails) This theorem is really useful for some of those stupid free ipad games. A REAL WORLD APPLICATION!!!
(about finding a Hamiltonian cycle in a graph) It's NP: Not my Problem
(someone asked how anyone came up with Konig's theorem) I don’t know what Germans did between 1850 and 1950 other than just drawing a bunch of bipartite graphs
(someone asked whether they could print their notes for the final) You can, you just can't bring them into the exam room
My friend Xavier (who sat next to me) and I would write these down in our notes as he said them, hence the recollection. But towards the end of the class, lecture started to get annoying because of the other people in it. There were two guys who would have their hands up constantly, not to ask questions, but just to show off to everyone else. One time a guy in the back said something along the lines of "so basically, let me predict what you're going to say" and my jaw was on the floor. The audacity of men in math. They need to be stopped.
Assignments were a lot of work, but rewarding, and I found the theorems in the course pretty easy to remember (unlike MAT301). My suspicion is that graph theory is easier to remember since it's so visually intuitive. The midterm was an online, open-note, take-home exam, my first since the pandemic. I didn't go about it particularly well; I wrote everything down and then typed it up in Latex like it was an assignment, which was a colossal waste of time, and I wound up having to submit the PDF three minutes before the deadline with an answer I knew was wrong. I was so concerned about the TA being able to read my handwriting that I sacrificed a problem's worth of marks, but oh well, I'm not as crazy as the person who apparently wrote and uploaded the whole thing in Expo marker on a whiteboard.
(about Eulerian trails) This theorem is really useful for some of those stupid free ipad games. A REAL WORLD APPLICATION!!!
(about finding a Hamiltonian cycle in a graph) It's NP: Not my Problem
(someone asked how anyone came up with Konig's theorem) I don’t know what Germans did between 1850 and 1950 other than just drawing a bunch of bipartite graphs
(someone asked whether they could print their notes for the final) You can, you just can't bring them into the exam room
My friend Xavier (who sat next to me) and I would write these down in our notes as he said them, hence the recollection. But towards the end of the class, lecture started to get annoying because of the other people in it. There were two guys who would have their hands up constantly, not to ask questions, but just to show off to everyone else. One time a guy in the back said something along the lines of "so basically, let me predict what you're going to say" and my jaw was on the floor. The audacity of men in math. They need to be stopped.
Assignments were a lot of work, but rewarding, and I found the theorems in the course pretty easy to remember (unlike MAT301). My suspicion is that graph theory is easier to remember since it's so visually intuitive. The midterm was an online, open-note, take-home exam, my first since the pandemic. I didn't go about it particularly well; I wrote everything down and then typed it up in Latex like it was an assignment, which was a colossal waste of time, and I wound up having to submit the PDF three minutes before the deadline with an answer I knew was wrong. I was so concerned about the TA being able to read my handwriting that I sacrificed a problem's worth of marks, but oh well, I'm not as crazy as the person who apparently wrote and uploaded the whole thing in Expo marker on a whiteboard.
CSC336 / Numerical Methods / Prof. Christina Christara
I did not enjoy this course at all. I think if you're already really passionate about numerical methods and scientific computing, then this is certainly the course for you, but if you (like me) signed up for it completely blind, you're in for a wild ride. The drop rate was over 30 per cent, and that was 30 per cent of students who had already self selected into that course. I'm honestly struggling to find a way to describe the CSC336 experience, and I think any description won't do it justice, so just look at the course website.
We had an Ed Discussion board, but we weren't allowed to ask anything academic on it, per the syllabus. The lecture slides, found at the bottom of the course website, were chock full of information. This is good for studying, but I found it really hard to actually keep up with the lecture in real time-- I've been spoiled by the math department's blackboards and real-time notes. I wound up annotating the slides on my own time outside of class. Assignments had an unnecessarily confusing set of format requirements and paragraphs of exposition before every question, but I did find the assignments useful in actually practicing the material. Also, Prof. Christara is a very kind (and quick!!!) grader and writes a good midterm. So going into the final, I was doing well. But oh boy were my fortunes about to turn.
I was sick the whole week leading up to the final, but I thought I studied pretty well anyway-- worked through all the tutorial problems, did two past exams, made flashcards to remember all the theorem conditions and formulas I needed. And I got above a 90 on all the assignments and an 87 on the midterm. How hard could it be?
Hard, it turns out. All the past exams online had nice numbers in the nonlinear equations and functions to interpolate, but on this exam, all the numbers had e in them. Most of the questions had some sort of hint about how you'd need the value of a certain quantity in terms of e, and my calculations almost never yielded that quantity. The second half of the exam was okay, but then I hit the last question, which was all MATLAB code about splines. I spent five minutes trying to parse what it was asking, and in my panic about how little time was left, I was more focused on how many marks I was going to lose than how to answer the question. I knew this was stupid and tried to tell myself so, but telling myself so also lost me time. I scribbled down answers I knew were wrong and hoped for the best. When the exam was over, and my exam had been collected and someone else's hadn't, I saw a bit of his answer to the last question and realized the question was just a weird way of asking an obvious question about splines that we'd worked with a lot on the assignments. I couldn't believe I'd missed it; I feel like there's a state of mind you go into at the end of an exam where if someone asked you what 2+2 was you wouldn't be able to answer. I just have to hope I got something in the 80s, I think.
I did not enjoy this course at all. I think if you're already really passionate about numerical methods and scientific computing, then this is certainly the course for you, but if you (like me) signed up for it completely blind, you're in for a wild ride. The drop rate was over 30 per cent, and that was 30 per cent of students who had already self selected into that course. I'm honestly struggling to find a way to describe the CSC336 experience, and I think any description won't do it justice, so just look at the course website.
We had an Ed Discussion board, but we weren't allowed to ask anything academic on it, per the syllabus. The lecture slides, found at the bottom of the course website, were chock full of information. This is good for studying, but I found it really hard to actually keep up with the lecture in real time-- I've been spoiled by the math department's blackboards and real-time notes. I wound up annotating the slides on my own time outside of class. Assignments had an unnecessarily confusing set of format requirements and paragraphs of exposition before every question, but I did find the assignments useful in actually practicing the material. Also, Prof. Christara is a very kind (and quick!!!) grader and writes a good midterm. So going into the final, I was doing well. But oh boy were my fortunes about to turn.
I was sick the whole week leading up to the final, but I thought I studied pretty well anyway-- worked through all the tutorial problems, did two past exams, made flashcards to remember all the theorem conditions and formulas I needed. And I got above a 90 on all the assignments and an 87 on the midterm. How hard could it be?
Hard, it turns out. All the past exams online had nice numbers in the nonlinear equations and functions to interpolate, but on this exam, all the numbers had e in them. Most of the questions had some sort of hint about how you'd need the value of a certain quantity in terms of e, and my calculations almost never yielded that quantity. The second half of the exam was okay, but then I hit the last question, which was all MATLAB code about splines. I spent five minutes trying to parse what it was asking, and in my panic about how little time was left, I was more focused on how many marks I was going to lose than how to answer the question. I knew this was stupid and tried to tell myself so, but telling myself so also lost me time. I scribbled down answers I knew were wrong and hoped for the best. When the exam was over, and my exam had been collected and someone else's hadn't, I saw a bit of his answer to the last question and realized the question was just a weird way of asking an obvious question about splines that we'd worked with a lot on the assignments. I couldn't believe I'd missed it; I feel like there's a state of mind you go into at the end of an exam where if someone asked you what 2+2 was you wouldn't be able to answer. I just have to hope I got something in the 80s, I think.
MAT344 / Introduction to Combinatorics / Prof. Jessica Liu
I signed up for the 6-8pm lecture, which was a massive mistake; when I had tech week for campus theatre shows, I would miss entire concepts. Even going to every lecture wouldn't have saved this course, though; I liked it a lot less than I thought I would. It felt like a high school class in spirit. You know how in high school, you just get a bunch of random math concepts thrown at you without much of a connecting thread or motivation? This course was like that. I mean, we obviously proved everything, but that doesn't really help with figuring out how everything fits together. I think this was mainly the textbook's fault; it was called Applied Combinatorics and it certainly was applied. Each chapter just jumped unceremoniously from example to example, with very little explanation. Also no answers to the exercises.
Prof. Liu is one of the most approachable and encouraging instructors I've had at UofT. She never dismissed or belittled anyone in class, even if they (read: if I) asked a stupid question. She usually said something like "you're on the right track!" See, other profs, is it so hard to just be nice? She was also very responsive via email, and posted pictures of her blackboard notes to the Quercus after every lecture, which was very helpful when I missed class.
The course structure was okay. The course coordinator, Prof. Stanislav Balchev, didn't have the Quercus up until week 2, and our assignments got pushed back as a result, which I guess was nice since it gave me a bit of a break early on in the semester. But we also didn't have the syllabus until week 2, which is just bad. I'm going to mention the marks breakdown for the first time, because my friend Avi and I were talking about it after the final, and we realized Prof. Balchev might have secretly designed the craziest generative AI policy at UofT.
So 40% of our final mark consisted of 4 assignments, each of which had insanely high averages (around 98%). I'll have you know I earned my good marks on those assignments fair and square. But the AI usage must have been through the roof. I remember thinking, why on earth are they giving us this much of our mark for free?
I didn't study as much as I wanted to for the midterm since it was the week of a campus theatre show I'd been working on for two weeks. But I walked away from it thinking I'd done pretty well-- I'd answered everything, checked my answers over, and finished an hour early. I got the mark back a month later and was shocked to see a 79%. Then, looking at the marks breakdown, I realized I got the highest mark in the early sitting. The average was around 45%, and the regular sitting average was even worse. The TAs took off almost half the total marks for a question for any minor mistakes, which just felt unfair. The final was quite a bit harder; I did the best I could and feel pretty confident in my answers, but who knows how harsh the grading will be. This is what Avi and I realized: the assignments are the curve for horrifically marked tests, and the horrifically marked tests are an adjustment for everyone (except me!!!!!!!) using AI on the assignments. Personally, I'd prefer a lot of fairly marked term tests to one midterm where they rob us blind. But at least I had a massive confidence boost seeing how far above average my midterm mark was.
I signed up for the 6-8pm lecture, which was a massive mistake; when I had tech week for campus theatre shows, I would miss entire concepts. Even going to every lecture wouldn't have saved this course, though; I liked it a lot less than I thought I would. It felt like a high school class in spirit. You know how in high school, you just get a bunch of random math concepts thrown at you without much of a connecting thread or motivation? This course was like that. I mean, we obviously proved everything, but that doesn't really help with figuring out how everything fits together. I think this was mainly the textbook's fault; it was called Applied Combinatorics and it certainly was applied. Each chapter just jumped unceremoniously from example to example, with very little explanation. Also no answers to the exercises.
Prof. Liu is one of the most approachable and encouraging instructors I've had at UofT. She never dismissed or belittled anyone in class, even if they (read: if I) asked a stupid question. She usually said something like "you're on the right track!" See, other profs, is it so hard to just be nice? She was also very responsive via email, and posted pictures of her blackboard notes to the Quercus after every lecture, which was very helpful when I missed class.
The course structure was okay. The course coordinator, Prof. Stanislav Balchev, didn't have the Quercus up until week 2, and our assignments got pushed back as a result, which I guess was nice since it gave me a bit of a break early on in the semester. But we also didn't have the syllabus until week 2, which is just bad. I'm going to mention the marks breakdown for the first time, because my friend Avi and I were talking about it after the final, and we realized Prof. Balchev might have secretly designed the craziest generative AI policy at UofT.
So 40% of our final mark consisted of 4 assignments, each of which had insanely high averages (around 98%). I'll have you know I earned my good marks on those assignments fair and square. But the AI usage must have been through the roof. I remember thinking, why on earth are they giving us this much of our mark for free?
I didn't study as much as I wanted to for the midterm since it was the week of a campus theatre show I'd been working on for two weeks. But I walked away from it thinking I'd done pretty well-- I'd answered everything, checked my answers over, and finished an hour early. I got the mark back a month later and was shocked to see a 79%. Then, looking at the marks breakdown, I realized I got the highest mark in the early sitting. The average was around 45%, and the regular sitting average was even worse. The TAs took off almost half the total marks for a question for any minor mistakes, which just felt unfair. The final was quite a bit harder; I did the best I could and feel pretty confident in my answers, but who knows how harsh the grading will be. This is what Avi and I realized: the assignments are the curve for horrifically marked tests, and the horrifically marked tests are an adjustment for everyone (except me!!!!!!!) using AI on the assignments. Personally, I'd prefer a lot of fairly marked term tests to one midterm where they rob us blind. But at least I had a massive confidence boost seeing how far above average my midterm mark was.