Course Advices for aspiring Quant?
Hey guys! I'm a first year undergrad at NYU Stern and quant seems really interesting. I really like statistics and probability along with computer science but I don't know exactly how I should be choosing my courses. I have taken a basic stats class(regression, permutations etc.) and I know basic java(methods, loops, recursion). From my research on this site, I know that I need cs skills for quant but can anyone tell me a course list I can just use. Do I need to take a machine learning class, should i keep taking java classes, or maybe I need to start taking set theory and diff eq classes? I saw a really interesting python class for basic data visualization so would that be useful to take? I really just want to find the right courses so I can be capable of passing interview and have the knowledge these firms want. Thanks so much for any advice
I will preface this by saying that I AM NOT A QUANT (so hopefully someone in the industry can chip in soon to correct me!!). However, here are some things I would imagine are useful skills to have:
- Coding: you should learn to code in Python; get familiar with working with large sets of data in projects and the standard libraries. Some firms also like knowledge of C++. Could take classes and then practice LeetCode to practice algorithms & data structures questions
- Machine learning: I would try to take classes in this if possible (not sure if a requirement, but I think it will be quite useful; also, its worth learning about while in college!)
Core Classes - that will be tested in interviews:
- Calc classes/ linear algebra
- algorithms & data structures
- probability theory
- stats (you said you have taken this)
- Game theory (although this is more for trading I think...)
- ML (if you are applying for QR, then am fairly sure they could test ML)
Extra ones:
- Bayesian statistics & inference
- Optimization
- Compilers/high performance computing (depends on the firm)
It depends on the type of quant you want to be, and what type of strategies you want to be working on. For alpha type roles, the faster the strategies the fancier statistics (ex: machine learning) you may potentially end up using. The bare minimum you need to know seems to be linear regression, for which you will need some linear algebra. But no one is going to ask you about machine learning unless you either a. claim you know it or b. the role explicitly requires it as part of the job function. More trading type jobs may ask you more probability/combinatorics type of brainteasers. If you go to high frequency trading (although I don't do this), I think a lot of the time its kind of like a developer job in that all that really matters is code speed (so you will need to be an A++ coder). For a pricing quant (ex: on an options desk at a bank) you may need stochastic calculus this type of stuff- but not in other quant roles. I think you can safely take what you find interesting, beyond the bare minimum of understanding basic statistics and developing functional programming skills (which does not necessarily have to come from very advanced classes), unless there is a particular area sub-focus you know you want to focus on within quant (but probably not).
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