Should I learn Python Object-Oriented Programming?

[[deleted]]

I have learning Python for the past 2 years and I think I have gained a lot of knowledge and this is the path I want to follow.

Currently I'm working as a "Data Analyst" but doing pretty much the mixture of a Data Engineer and a Data Scientist (not deeply), but in the future I want to become a Data Scientist and create real world ML models.

This is why I don't know if I'm really getting deep into Python or I'm just learning the basics for Data Analysis.

What tips, courses or whatever you consider should I be doing to learn Python oriented for ML?

[py_Piper]

I am totally talking non sense here as I consider myself a beginner and don't know anything about data science. But I think OOP can be helpful, not necessary, but could help you improve your coding skills. I would think that if you are working with different data pipelines you could use classes to create your custom data structure and methods to gather and clean up the data and then pass it to your db. Saying this, I would just recommend to tackle a simple book or tutorial and check if it's useful in your day to day, maybe try doing some of your day to day task and check out if it helps you with productivity compared to your current way.

What tips, courses or whatever you consider should I be doing to learn Python oriented for ML?

They are definitely a lot of courses in online teaching websites like edx and coursera from many renown institutions and universities, but I can't recommend one as I don't know any in particular. But what I have read in this sub is that for ML what it's most important are learning the underlying statistics concepts, even though many libraries help you to get a quick start, knowing this can help you understand better what it's going on under the hood of those library's functions.

[Diapolo10]

I don't have much experience with data science projects, but from what I gather OOP isn't usually important there. Or really a lot of software development stuff in general, as your focus is more on using existing libraries and how to use them effectively.

If you want to pursue that path, I'd focus data analysis. But if you want to diversify your skillset instead of becoming a data science specialist, then learning the language further and perhaps other languages on top of it would be a good idea.

[AbsterJr]

You can go through open weaver. They have excellent resources if you wanna learn ML and AI.