The first time I heard about AI was when I was playing games when I was little. The “AI” were the enemies I had to encounter and defeat. I took it as it was: a slider or a beginning choice that decided how hard I want the game to be against me – from easy to hard.

In high-school, we learned a lot of math – sadly, not how it is or can be applied in the real world and its uses – but didn’t get too much the hang of it deeply, so to say, to really understand the meaning behind it:

• Firstly, because we were constantly pressed by the Bacalaureat and the performance we had “to prove” there
• Secondly, because the curriculum doesn’t cover the “philosophy” behind math and its uses… which, to say the least, it’s a pity

You are forced by circumstances to choose between two options:

1. (Try to) Study by yourself the history and uses of sciences that you learn at school, “losing” time while you can memorize and solve endlessly the way to solve integrals in a short period of time
2. Cope with the system that wants you only to know what you have to do at the Bacalaureat and pray that maybe, at some point, some professor in Faculty, a project or whatever YouTube video you see randomly at 12AM, makes you interested and intrigued enough to make you research by yourself in your then spare time.

I personally chose option 2, which focuses on “immediate survival“: I wanted and needed to get to the Faculty I wanted, so the other option could wait for a more opportune time..

Luckily, the 18-year-old that analyzed and chose the faculty didn’t do a mistake by choosing it.. (per se)

The metaphor seems to be the same everywhere, even abroad in more developed contries: “Here’s the curriculum. I will teach you this, test you after, that’s your performance.. no one pays me extra for showing you how it works (maybe even I don’t know that either) and I won’t do that anyway.”

This makes engineering or science majors even more difficult and time-consuming. How can I understand how something works if I am not shown how it work by someone who LIKES and UNDERSTANDS IT more than the salary they receive or the more or less bad choices they did in the past thinking that being a professor might be fun. ⚠️(DISCLAIMER, working with people requires LOTS of patience and to deeply understand a simple concept: making it interesting and appealing for those who already are interested in your subject doesn’t prove your “worth” as a professor; yet making the ones that didn’t knew a bit about it before attending your class and taking their attention and stimulating their curiosity in the subject, is the real satisfaction)⚠️

Due to my highly optimistic view, I get TURBO-motivated and curious when I encounter such professors – that make me curious and interested in their subject even though it maybe didn’t align with my future interests, attractions or past knowledge – and I encountered a few here. With the rest, I adapt with it over time.

During the 1st year of Bachelor’s, we studied lots of maths: calculus and linear algebra 🥁*drumrolls*🥁 (which are heavily used in AI/ML – will talk about it in a bit) ; at times, we were presented with the in-and-outs of the concepts presented; other times, pressed by the approaching exam session, went like tornadoes into them. This made it even harder to grasp university-grade concepts about other stuff we studied too.. But I adapted and did what I had to do.

My AI/ML journey stared in my 3rd year of Bachelor’s