I took 16 ECTS this semester.
| Course Name | Teacher | ECTS | Score |
|---|---|---|---|
| History of Economics | Béatrice CHERRIER | 3 | A |
| Machine Learning | Jesse READ | 5 | A |
| Econometrics | Laura RECUERO VIRTO & Arne UHLENDORFF | 5 | A |
| Intermediate French (B1/B2) | Marie-Chantal GERARD | 2 | A |
| Sports - Year 2 (Racketlon) | 1 | A+ |
History of Economics
Less my personal peak than the peak of my course-selection luck. The format was role-playing debates on a set of given topics. My group went first, on “is economics too mathematized?” — a spicy thing to argue as a math major (and worth noting that BX students all double-major, one of which must be mathematics). I was on the affirmative: that economics piles on complex models that still do not prove all that useful — which of course turns straight into a fight over what “useful” even means. Being week one, the room had not warmed up yet; later weeks were livelier, with topics like “is economics objective?” and “is economics too ideological?”. I like logical debate — not the angle-switching sophistry of competitive debating, which is pointless here and gets called out on the spot. More than anything, this course taught me how to think, and how to write something a reader can actually follow.
Machine Learning
A standard machine learning course in Python. The final project became my Credit Card Default Prediction Using Machine Learning project, and it is fairly low-stress — you present slides and interpret your results rather than walk through the code in detail. The practical lessons that stuck were small but real: stratify your train/test split, and actually interpret the data instead of just reporting a score.
Econometrics
My applied-math background genuinely helped here — most of it is simple intuition. R was new to me, though it is not tested on exams; Pierre mainly introduced it as a tool, and I still remember him teaching earnestly even when the room clearly was not listening (I felt a little sorry for him). My interest in actuarial work actually predated this course, so it did not spark that — but the final quarter, on panel data, time series, and handling economic data, opened up a set of new tools (fixed effects, first-differencing) and new territory. It is the reason I went on to take Time Series.
Intermediate French (B1/B2)
Not much to say. It didn’t feel especially “intermediate” — the class dipped into a bit of everything from A2 to B2, without a clear through-line or a few solid themes to build on.
Sports - Year 2 (Racketlon)
About 30 students share a big indoor hall (eight badminton courts), with outdoor tennis courts too. Attendance is enough to pass, though the instructors do push you to actually play.