Math W53: Multivariable Calculus

Pretty cool class with interesting ideas but I found that none of them really stuck as there were virtually no proofs involved. This video sums up the big idea pretty nicely.

Math 54: Linear Algebra and Differential Equations

The best parts of this class for me were the applications. Finding a closed form formula for the Fibonacci sequence was particularly enlightening. I used this class as an opportunity to dive deep into the statistical interpretation of the singular value decomposition, which led me to participate in a directed reading program related to mathematical foundations of data science.

Math 55: Discrete Mathematics

Easily the most interesting lower divison math class. Prof. Nikhil Srivastava was amazing and I enjoyed his emphasis on graph theory even though it was tough. Though most of the number theory was review for me, I felt that the proofs I learned in this class were what really made everything click.

Math H110: Honors Linear Algebra

Linear algebra is actually so cool. This class made me realize that abstraction is a big part of what makes math so powerful. I particularly enjoyed the connection between algebra/number theory and linear algebra through minimal polynomials, and the connection between analysis and linear algebra through the Riesz representation theorem. I have detailed notes here.

Math H104: Honors Introduction to Analysis

Taking this class this fall. Looking forward to it.

CS 61A: Structure and Interpretation of Computer Programs

The exams were nothing like any exam I'd taken after moving to the US. Almost felt like an AMC-type exam. My eye for reading code definitely got better after this class and I got much more comfortable dealing with abstraction and OOP.

CS 61B: Data Structures

There were some pretty cool ideas in this class. One particular one that comes to mind is the sentinel node for linked lists. Such an aesthetically pleasing and mathematically nice idea. The software engineering aspect was helpful but painful and I've marked it as an area for improvement.

CS 61C: Great Ideas in Computer Architecture (Machine Structures)

Made me realize that computer hardware and engineering in general is probably not for me. The various methods for optimization felt unnatural and unintuitive. Creating something so powerful like a computer from the ground up is appealing but unsurprisingly a very painful task. Learning about error correcting codes and their relation to sphere packing problems was pretty cool.

EECS 126: Probability and Random Processes

May or may not get off the waitlist this fall..

Data 8: Foundations of Data Science

I found that I like the math behind probability and statistics more than the actual inference process used to generate useful information. This is perhaps somewhat unfortunate as the latter is much more easily monetizable.

Philosophy 116: Special Topics in Political Philosophy

Taking this class this fall. Looking forward to it.

Physics 5A: Mechanics and Special Relativity

Probably the hardest class I took in my first year. I took it because I wanted to see if I liked physics. I was left with very mixed opinions after the class. The ideas in the class were very interesting: that any energy function can be decomposed into something that resembles kinetic + potential energy and is mathematically equivalent to a set of harmonic oscillators under small perturbations; rotational inertia, the inertia matrix, the principal axis theorem and its application of the spectral theorem; gyroscopes and their unintuitive behavior; reduced mass and solving the two body problem; and the incredibly unintuitive yet mathematically elegant ideas and consequences of special relativity. However, the process of getting to these ideas was so painful and I found that physical intuition didn't come naturally to me.