Disappointing curriculum – what to do next?

Electrumite

New Member
Last year, I have started an MSc Finance and am a little disappointed with the curriculum. Don't get me wrong, the courses sounded great and very useful in becoming a quant a.k.a. "Quantitative AI data science machine learning technology course" (I'm exaggerating, but you get the point) but they were mostly not rigorous at all.
I am aware that an MFE would've been the better choice but even though I had plenty of math/stats courses in my undergrad, the degree I received was still a "BA Business and Economics", which apparently disqualified me for the programmes that I was interested in. I will graduate next year when I'll be 24.

The question is: What do I do from here? The main problem is that even if I start applying to jobs, it will be difficult to break into the field and even if I would, for some reason, get in, I do not feel adequately trained.

From my point of view, there are 3 options that I have:

  • Apply to a PhD
    • Pros: I learn the skills and might have an advantage for certain roles​
    • Cons: It is hard to get accepted, it takes an insanely long time (5+ years) and I don't know how big or if there is even an advantage for most roles (over people with MFEs)​

  • Apply to MFE
    • Pros: Easier to get in than PhD, good training for later and strong signal​
    • Cons: 2 more years of studying and might seem redundant to an employer to have 2 finance degrees​

  • Apply for Applied Math MSc
    • Pros: Most likely the easiest to get in, learning the necessary skills and strong signal​
    • Cons: Usually takes 2 years and I'm not sure whether I would then have a chance to break in without an MFE or PhD; it is also hard, which means that I expect lower grades than with the other options.​



I know that I will have to decide in the end, I am just curious of whether you have any comments or what you would do if you were in my situation. Thank you.
 

Daniel Duffy

C++ author, trainer
"Quantitative AI data science machine learning technology course"

Which version number/release of this <product>?

The title is tautologous.
 

Electrumite

New Member
"Quantitative AI data science machine learning technology course"

Which version number/release of this <product>?

The title is tautologous.
I deliberately chose an exaggerated title to emphasize my point that most courses sounded very useful but my hopes of learning useful skills and theory about ML, quantitative finance etc. were all but fulfilled. Of course, "Quantitative AI data science machine learning technology course" as a course itself does (to the best of my knowledge) not exist and I apologize if that title is misleading.
 
Top