I didn't realize I would write a five-part post for May, so this April blog post will just be a skeleton for now. I'll add the meat and flesh after I'm done my epic.
MATH 152: Linear Systems
Elyse Yeager, 2015W2, 94%
2D and 3D geometry, vectors and matrices, eigenvalues and vibration, physical applications. Laboratories demonstrate computer solutions of large systems.
This is basically MATH 221 for engineers. Elyse was probably my best math prof ever. This was her first term teaching in UBC and it was fantastic. Hordes of students would flock to her section even though it was at 8:00 am. I think she gave like hands-on demonstrations and stuff, and her slides were way better than everyone else's (and also they existed, unlike everyone else's). Unfortunately the actual students in her section often wouldn't show up and her section ended up having the lowest average overall lmao
MATH 217: Multivariable and Vector Calculus
James Colliander, 2015W1, 93%
Partial differentiation, extreme values, multiple integration, vector fields, line and surface integrals, the divergence theorem, Green's and Stokes' theorems. Intended for students in Honours Physics and Engineering Physics.
This is basically MATH 200/253 + MATH 317 for honours physics. took this in first term first year cause I took IB credits for MATH 100 and MATH 101. Boy what a mistake, IB math did not prepare me for vector calculus at all! I studied my butt off for this, I must've gone through every practice problem in the book. It was also James Colliander's first term teaching at UBC, but he was way too idealistic for us jaded second-year students. Nobody understood anything he said in his lectures, he was like my high school math teacher who made us write poems about math and watch movies completely unrelated about math because traditional textbook learning was just rote memorization. But then the final ended up being traditional textbook problems anyway, so everyone who played around in his course thinking about how cool and transcendent math was got absolutely screwed in the final, and I got scaled up to 93%. He followed me on GitHub cause I made this one commit on the course webpage. Yeah, he called the final project an "epic". But you really ought to read my May blog post to see a real epic...
MATH 255: Ordinary Differential Equations
Emmanouil Daskalakis, 2016W1, 93%
Review of linear systems; nonlinear equations and applications; phase plane analysis; Laplace transforms; numerical methods.
This was cross-listed with MATH 215 so I finally got to sit with some of my high school friends that went into Science instead. I remember absolutely nothing about this course and even less about the lecturer. I think I ended up going to Richard Froese's lectures more, since he's the father of my friend, and I couldn't understand anything my actual lecturer was saying. Easy peasy course, I have no idea why they don't let us take MATH 256 instead, which is basically MATH 255 + MATH 257.
MATH 257: Partial Differential Equations
Ian Frigaard, 2017S1, 82%
Introduction to partial differential equations; Fourier series; the heat, wave and potential equations; boundary-value problems; numerical methods.
This was cross-listed with MATH 316 but none of my Science friends took summer classes. I don't know why I did so badly in this course, though it's the second-best mark I got in that accursed robot summer. Probably it was because I never went to lectures. Everything we learned in this course we covered again in more detail in MATH 400, so I really don't know what the point was. If you have Frigaard, remember to keep your cheat sheets. I think he gives you half a page for each quiz, there's four quizzes, and he gives you two pages for the final, so you can just bring the cheat sheets you already wrote for the quizzes, to the final.
MATH 305: Applied Complex Analysis
Sven Bachmann, 2017W2, 84%
Functions of a complex variable, Cauchy-Riemann equations, contour integration, Laurent series, residues, integrals of multi-valued functions, Fourier transforms.
This is basically MATH 300 for engineers. I swear I must have gotten 60% on the final or something ridiculous. Super interesting course that becomes super boring at the end, when you find out the only "application" of complex analysis is evaluating improper integrals of complicated (not complex) trigonometric functions. I'd honestly recommend reading the textbook, but don't waste your time on the course. We got to sit in a classy pharm classroom for this, which was absolutely fabulous, but the walk from Hennings was not.
MATH 307: Applied Linear Algebra
Kalle Karu, 2017W2, 96% (highest in section)
Applications of linear algebra to problems in science and engineering; use of computer algebra systems for solving problems in linear algebra.
I swear I must have gotten 150% on the final or something ridiculous. I never went to class, not even to hand in homework (I always got a different friend to hand it in each week), and was aiming for something in the high 80s. An hour before the final, I still had no idea what singular value decomposition was. An hour after the final, I also had no idea. Honestly, I have absolutely no idea how I got the highest mark, but didn't bother to ask if it was a mistake. Probably balances out the mistakes I made in MATH 305.
MATH 318: Probability with Physical Applications
Geoffrey Schiebinger, 2019W2, 94%
Random variables, discrete and continuous distributions. Random walk, Markov chains, Monte Carlo methods. Characteristic functions, limit laws.
This is basically MATH 302 + MATH 303. I was hoping to get 99% in this, but screwed up in the first midterm, and when everything went online there was no way to get any bonus marks from scaling, so I ended up with this. Probably the most interesting math course I took at UBC.
MATH 320: Real Variables I
Gordon Slade, 2017W1, 80%
The real number system; real Euclidean n-space; open, closed, compact, and connected sets; Bolzano-Weierstrass theorem; sequences and series. Continuity and uniform continuity. Differentiability and mean-value theorems.
You can take this without MATH 221 if you register for the minor in honours mathematics, which you can just drop immediately after. If you know how to write a proof, this is really not bad. There aren't that many problems in baby Rudin, and it's definitely feasible to do all of them. I got through almost half the day before the final, and half the questions on the final were from the half I already did, and I'm pretty sure the other half was from the half I didn't do. So if you do all the problems, you can get 100%. Analysis was just not that interesting to me though. I guess cause it wasn't "applied".
MATH 400: Applied Partial Differential Equations
Juncheng Wei, 2019W1, 89%
Separation of variables, first order equations, Sturm-Liouville theory, integral transform methods.
Absolutely pointless course. If they didn't cram MATH 257 into a summer term we could have absolutely covered everything then, except for maybe the useless first-order nonsense. I screwed up on the midterms and assignments, but got 97% on the final. Thank god that was worth more than 5%!
tl;dr: uh ill fix this up later