NR Classes

Every Data Scientist, every ML Engineer, every Analyst — they all started the same way.
Opening a file.
Not a neural network. Not a transformer model. Not a fancy API. Just a simple .csv file.
CSV — Comma Separated Values. The most basic, most universal, most underrated data format in the world. And if you can't read it with Python, nothing else matters.
Here's the thing most courses won't tell you — before you learn pandas, before you touch dataframes, you should know how Python reads a file at the raw level.
import csv → open the file → read row by row → understand the structure.
That's it. No magic. No library doing the thinking for you. Just you, the file, and a for loop.
Why does this matter?
Because in interviews, when they ask "how would you handle a corrupted CSV?" — pandas won't save you. Understanding how csv.reader() works line by line will.
Because in production, when a 2GB file breaks your memory — knowing the raw reading approach gives you control.
Because every big thing in data starts small. And this is the smallest, most powerful first step.
Master the basics. The advanced stuff becomes easy.

Recursion is important while preparing for the interview. Here is the demonstration of how we use recursion to find out GCD of a number. This is not a good technique if there is a big difference in the numbers.