I Survived GCI

I finally did it. I completed the GCI Matsuo Iwasawa Course, offered by the Matsuo-Iwasawa Lab at the University of Tokyo.

And when I say completed, I mean actually completed.

There were nights where it was 3 AM and I was still staring at my model, trying to squeeze just a little more out of the AUC score.

0.78.

No.

0.81.

Okay, we're getting somewhere.

Then somehow I’d end up with a good rank on the leaderboard, convince myself I had finally figured things out, take a “quick” two-hour nap...

...and wake up at the bottom.

THE PAIN.

Back to the model.

But that's probably one of the things I enjoyed most about GCI. It wasn't just about learning the theory. It was about actually having to experiment, make terrible models, improve them, question your results, and try again.

And somewhere between the Python, machine learning, data analysis, competitions, late nights, and questionable sleep schedules, I realized that I was getting closer to the kind of AI engineer I want to become.

Someone who can identify a problem, analyze the factors contributing to it, and come up with a solution, even if getting there involves late nights, many failed experiments, and a questionable amount of caffeine.

A Deep Learning Engineer.

So, one course down.

There is still a ridiculous amount left to learn.

But we're getting there.

If you're interested in AI, Machine Learning, Data Science, or Python, I genuinely recommend checking out GCI.

Applications are currently open through the University of Tokyo's Matsuo-Iwasawa Laboratory.

You can apply here, and hopefully gain some fun experiences like I did: GCI Application

And if you apply, you can use my referral code:

LN8CQF

Maybe I'll see you on the leaderboard.

Hopefully somewhere above me this time.