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MSc advice

  • Thread starter Thread starter Gaius
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Hello,

I would like to know what anyone thinks about the MSc in Applied Computational Science and Engineering at Imperial College, does it look like a solid MSc in terms of content for someone wanting to go for quant research roles? It contains the following courses: Data Science and Machine Learning, Deep Learning, Inversion and Optimisation, Modelling and Numerical Methods, Modern Programming (Python), Patterns for Parallel Programming (C++), Advanced Programming (C++), Computational Mathematics.
I have a BS in maths and 3 years of experience in risk where I did some coding in Python, I am looking to strenghten my statistics and data science skills and l thought this looked like an interesting program but I'm not sure how useful most of these courses will be.
 
Last edited:
Hi there,

I'd say any of the math degrees at ICL are top-notch. It really depends on whether you're more interested in data-driven modelling or stochastic differential equations. But in some cases, fancy quant boutiques might ask for both.
 
Hi there,

I'd say any of the math degrees at ICL are top-notch. It really depends on whether you're more interested in data-driven modelling or stochastic differential equations. But in some cases, fancy quant boutiques might ask for both.
Thanks for the reply. I was asking because I am hesitating between this one and the MSc in Statistics. They are both interesting but it seems to me the statistics one would be a bit more useful for research roles. Do you think it is a significant advantage to take more statistics classes (time series, multivariate analysis and non parametric statistics for example) instead of the C++ ones in the ACSE degree if I am more interested in data driven modelling or does it make little difference at this stage?
 
If you're more interested in data-driven modelling, more statistics classes like time series and stuff could be more advantageous for research roles. I'd say that any MSc isn't the pinnacle. Still reality requires to do 80% of the work yourself. If you find it easy to learn C++ on your own, focus on statistics, or vice versa.
 
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