Should I take PDE before MFE?

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An mfe is totally fucking useless. I have one. Way too overrated. Doesn't even help you land a interview. Most prefer people from a physics background. Just get a ms in cs or math from a top school and ur fine. An mfe is just a way to make money from u while teaching u useless real world skills
MFE from what school? Highly ranked? Why do you say is useless? Did the school help you find a job?

Did you learn anything useful in the MFE? Coding? Risk? Finance?
 
An mfe is totally fucking useless. I have one. Way too overrated. Doesn't even help you land a interview. Most prefer people from a physics background. Just get a ms in cs or math from a top school and ur fine. An mfe is just a way to make money from u while teaching u useless real world skills

Hi rajanS, did you graduate from the Baruch MFE program? What are your impressions? Are you saying it wasn't worth the time and money and wouldn't have done it knowing what you know now?
 
You're welcome
Many C++ quant library have a PDE engine and building your numerical knowledge incrementally will ease the transition.

A good model problem to learn is 1-factor heat equation using Crank-Nicolson and take it from there. If you understand the steps then you are well on your way to PDE Nirvana :)
https://en.wikipedia.org/wiki/Crank–Nicolson_method
Are PDEs, FDMs and numerical methods implemented only in C++? Or do they have some use with python?
 
Long story short: PDE libraries in Python has NO point. Python wasn't built for that. Libraries are built by C++ programmers and used by Python developers.
Got it. So basically all that math has no use for quant roles without C++??
Also, what is your take on the importance of scientific computing for quant roles?
And the importance of courses like bayesian stats,statistical machine learning, or AI/ML for quants?
 
Got it. So basically all that math has no use for quant roles without C++??
Also, what is your take on the importance of scientific computing for quant roles?
And the importance of courses like bayesian stats,statistical machine learning, or AI/ML for quants?
These *binary* questions are drifting from the initial question. Too general.

For PDE/FDM C++ is good,
However, a great way to learn FDM is to write prototypes in Python.
 
TBD, scientific computing can mean anything.
Do you mean 'programming'?
This is the course description:-
"Introduction to computation on digital computers. Design and analysis of numerical algorithms. Numerical solution of equations, integration, recurrences, chaos, differential equations. Introduction to Monte Carlo methods. Properties of floating point arithmetic. Applications to weather prediction, computational finance, computational science and computational engineering."
 
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