dev.study #01 - Learning NumPy, Arrays & Boolean Indexing

I'm currently participating in GCI World 2026, a Data Science program offered by the University of Tokyo's Matsuo-Iwasawa Laboratory.

Coming from a PHP development background, exploring Python for Data Science has been a new and exciting experience!

What I learned this week

• NumPy Arrays — Performing mathematical operations efficiently.
• Indexing & Slicing — Accessing specific elements and ranges.
• Multidimensional Arrays — Working with rows, columns, and matrices.
• Boolean Indexing — Filtering arrays using conditions.

A little code snippet

One of our homework exercises was to filter an array and return only odd numbers divisible by 5.

def homework(a):
    return a[(a % 5 == 0) & (a % 2 == 1)]

Simple, but a great way to understand how Boolean indexing works without writing loops!

Learning beyond Python 🌎

Another challenge? The entire program is taught in English!

As a Brazilian developer, I'm not only learning Data Science but also improving my technical English and connecting with people from different countries.

Sometimes it's challenging, but that's exactly what makes this experience worthwhile.

Python, Data Science, and English — all at once.

One lecture at a time. 💗

Thank you, GCI World, for this opportunity!