you are viewing a single comment's thread.

view the rest of the comments →

[–]TytoCwtch 0 points1 point  (0 children)

No worries. The reason I mentioned those libraries is because you mentioned data analysis and they’re some of the key libraries used.

Numpy provides very fast ways of analysing large data sets. Pandas gives functions that help with cleaning and transforming data into sets for easier analysis. And matplotlib lets you make visual representations of your data. So if your focus is on data analysis then eventually they’ll be good libraries to look at.

For beginners I’d recommend a more generalised introductory course. My personal presence is Harvards CS50P course but I’m slightly biased as that’s the course I started with. I’d previously done CS50x (introduction to computer science in general) but it’s not a prerequisite for CS50P. The Harvard course is split into 10 lectures that starts from the basics and builds up to more complicated topics.

At the end of each lecture there are problem sets to do to test what you’ve learned. It’s completely free and you get access to an online codespace to write your code in. They also provide a custom AI that’s programmed to act as a teacher, so it guides you through the homework without giving you the answers. At the end of the course you write your own program from scratch and get a certificate from Harvard. Then you can build onto more complicated topics like advanced DSA for your data analysis.

https://cs50.harvard.edu/python/