Today I enrolled in a Quantum Machine Learning course. It is offered by the University of Toronto free through edX.

Honestly, this course is probably way over my head. After all, I just started studying Machine Learning and Python just a few months ago.

However, where would any of us ever get if we never challenged ourselves? At a minimum, I’ll learn something. Hopefully, I’ll eventually be able to boast a passing grade, as well.

My first observation of the course is that, incredibly, you can do QML simulations from a smartphone. It’s not real QML yet, but that is obviously the end goal. Coding is done via online Jupyter Notebooks, which I am already familiar with.

My second observation is that the primary lecturer is not a native English speaker; his pronunciation can make the videos even harder to understand than the subject matter should by default. Fortunately, all the videos so far have transcripts so students can follow along.

On the subject of other students, it is evident in the discussions that other students have a lot more knowledge of quantum mechanics and linear algebra than I do. I’m not completely clueless, but I’ll be doing a lot of side research to keep up.

My third observation is that studying Quantum Machine Learning makes you hungry. That’s actually not surprising, considering the percentage of the body’s energy that the brain consumes.

As day 1 wraps up, I take consolation that, so far, the material is easier to understand than NASM (Assembly Language). Unfortunately, that’s not much consolation.

The course is self-paced for two months, so I — hopefully — have plenty of time to feel comparatively less stupid.