What are some interesting areas of math to study beyond calculus?
I am a typical computer science person, having studied the typical math topics an undergraduate would study. The topic area I spent the most time on (besides computer science) would be calculus. I have been out of college for a few years, but I find myself missing mathematics. What are some topics/areas of math that I didn't know I needed in my life? Doesn't have to be practical, could be purely for intellectual interest. But practical/useful topics would be welcome too of course.
Here are some things I have already studied:
- Calculus
- Differential, Integral, Sequences and Series, Vector (partial differential equations, gradients, Lagrange multipliers)
- Statistics and Probability basics
- normal distributions, hypothesis testing ("rejecting null hypothesis"), combinations/permutations
- Linear Algebra
- matrices, vector spaces
- Abstract algebra concepts from my studies in Functional Programming
- monads, monoids, higher order functions
- Discrete Structures and other CS stuff
- proof theory, set theory basics, logic, boolean algebra, graph theory
- Computer Science
- Deterministic Finite Automata, Grammars, Turing Machines (and Chomsky hierarchy of languages)
- Fractals, Cellular Automata
- Algorithms and analysis of algorithms
- alternative number system: base 2 number system (binary)
Recommend me something new!
16 comments
[ 5.2 ms ] story [ 47.8 ms ] threadhttps://en.wikipedia.org/wiki/Ulam_spiral
Mathematical Logic also looks interesting, especially from a historical perspective.
Please also check out "Gödel, Escher and Bach" if you haven't done so.
Just a note that studying Mathematics, especially tough topics needs a lot of discipline, time and energy, so be prepared mentally and physically. I don't think it's something one can do one hour daily and accumulate. Without many hours of study the more difficult topics just don't stick.
A proof-based linear algebra course would be the next course that is typical in the progression. If you've already done that, then an introductory real analysis course.
If you want something a bit more practical then maybe a probabilistic modeling course? ( think Gaussian mixture models, bayesian networks, plate models).
My personal recommendation would be to cover functional programming from the ground up. I consider the benefits of learning this as enormous for me.
The linked pages from that DDG search are mostly the reading list for BEFORE you attend and the reading list per class is not found like this.
On the other hand you can go directly to video lectures a MIT open courseware, and others, and most recently a great resource for pure mathematics is:
https://courses.maths.ox.ac.uk/course/view.php?id=1051
wherein the courses are split by the old term names/tripos:
Michaelmas Hilary Trinity
https://courses.maths.ox.ac.uk/course/index.php
Also, if you are interested in more sophisticated ways of capturing quantum physics, geometric algebra is really cool.
https://softwarefoundations.cis.upenn.edu/
It will not only make you a better software developer (by improving how you think) it will also show you how to prove software correct. And it is fun!
See page 15 of this PDF for his treatment of eigenvectors: https://linear.axler.net/Eigenvalues.pdf
There is one course on MIT Opencourseware that teaches it: https://ocw.mit.edu/courses/18-098-street-fighting-mathemati...
The book used in the course is also very good. The author is the same as the course instructor Prof Sanjoy Mahajan.