University of Toronto - Master of Mathematical Finance

The MMF program at U of T is undeniably one of the top two quantitative finance programs in Canada (the other being MQF at Waterloo).

The format of the program is one fall semester followed by an internship in the winter and ends with a summer semester.

The curriculum has a number of courses and workshops that are one day, one week or two weeks long. The topics range from ESG to blockchain to risk management to trading simulations, etc. And then you also have a handful of standard 12-15 week long courses on standard topics like stochastic calculus, derivative pricing, data science/ML, etc.

Hear this. The job market in Toronto has a VERY small number of quant jobs compared to New York and London. This is why many of the graduates land jobs in fintech, risk management, model validation, reporting, and generally less "quanty" jobs. Only a few of the top students get highly quantitative roles. For example on the buy side in one of the Canadian pension funds or front office quant roles on the sell side in one of tbe Canadian big six banks.

Given the job market in Toronto, the MMF program focuses on teaching students a good deal more about the "hot" topics and the skills that actually get students employed. A few of the students are disappointed that they don't learn all that much about programming or quantitative skills. But the program's curriculum is a product of the job market.

The program does a great job of getting everyone an internship in their winter semester. They have connections with many of the large companies in Toronto and send a resume book to each one in the fall. They are somewhat helpful when it comes to finding full-time jobs after graduation (of which there are very few) but much less so than for the internships.