Am I missing any math/cs from my undergrad coursework?

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Hey guys. I'm currently an undergrad in a Canadian university that gives a HUGE degree of freedom to customizing your own undergrad coursework. The only type of subjects I find interesting so far (besides humanities) is proving abstract mathematical theorems, as I find it beautiful and artistic. I got a 92 and 100 on Proof based Calculus and Proof based Linear Algebra respectively, so I thought I might as well try to break into quant (coding for me is like meh, but it come naturally, I got a 95 on first year into to programming course). With that goal in mind, I did some research on the top quant masters and tailored my coursework like the following:

Linear Algebra II (MAT224H1)

Introduction to Computer Science (CSC148H1)

Probability and Statistics II (STA261H1)

Concepts in Abstract Mathematics (MAT246H1)

Mathematical Expression and Reasoning for Computer Science (CSC165H1)

Multivariable Calculus with Proofs (MAT237Y1)

Introduction to Real Analysis (MAT337H1)

Software Design (CSC207H1)

Introduction to the Theory of Computation (CSC236H1)

Methods of Data Analysis I (STA302H1)

Introduction to Databases (CSC343H1)

Statistical Methods for Machine Learning I (STA314H1)

Algorithm Design, Analysis & Complexity (CSC373H1)

Data Structures and Analysis (CSC263H1)

Neural Networks and Deep Learning (CSC413H1)

Statistical Methods for Machine Learning II (STA414H1)

Time Series Analysis (STA457H1)

Methods for Multivariate Data (STA437H1)

Nonlinear Optimization (APM462H1)

Probability Theory (STA347H1)


I will also be practicing coding in Python and SQL (ideally C++ too), doing the Yale Financial Market Coursera, and reading about microeconomics and Options, Futures and Derivatives on the side, as well as getting involved in the school's quant finance club & events, along with documenting my own experimental trading.

Now my question is: Am I missing anything in this coursework, as far as MFE/Quant programs admission is concerned? The only gap I could see is Differential Equations, so I'm planning to take Online Courses over the next few summers to bridge it. Any suggestions are welcome, feel free to share your thoughts!

Thanks in advance.
 
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Maybe there isn’t much point in take a formal Course in Deep Learning (CSC413) during undergrad?
 
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ODE/PDE
Numerical Analysis, e.g. Numerical Linear Algebra.
QN C++/Python

Hi Daniel,
Thanks so much for the link!!
Do you think Online Courses
Would satisfy the Numerical Analysis requirements?
I’m also starting to think maybe it’s easier to change my coursework to include credits in ODE, PDE and Numerical Methods. Do you think any of the courses are unnecessary and can be replaced by Numercial Methods, etc.? Thanks!
 
Maybe there isn’t much point in take a formal Course in Deep Learning (CSC413) during undergrad?
I agree; DL is not fundamental knowledge; will DL be around in 5 years time?

"DL, (numeric) maths inside"

I have two numerics online offerings.
 
Hi Daniel,
Thanks so much for the link!!
Do you think Online Courses
Would satisfy the Numerical Analysis requirements?
I’m also starting to think maybe it’s easier to change my coursework to include credits in ODE, PDE and Numerical Methods. Do you think any of the courses are unnecessary and can be replaced by Numercial Methods, etc.? Thanks!
My 2 cents.
I am sure my online course AMP is hands-on, rigorous and unique (I did it numerical analysis in academia and industry since 1974).
Your initial list could include more of the "hard" maths IMO. It is future-proof.
 
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