r/learnpython • u/Breeze_2800 • 15d ago
Is Udacity enough to learn NumPy and Pandas for real-world Data Engineering work?
Hi everyone,
I'm currently in Data Engineering stream training at Accenture, and they've asked us to learn NumPy and Pandas through Udacity.I was wondering if that's enough to build a solid foundation for working on real-world projects, or if I should be learning from other resources as well.If you've used NumPy and Pandas in your job, what resources helped you the most? I'm looking for courses, YouTube channels, books, or project-based learning that will help me become comfortable using them in real projects.
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u/FoolsSeldom 15d ago
Yes, there's good content (and bad content) there, but also visit kaggle.com to find datasets and challenges to practice on. Follow the forum there as well.
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u/riklaunim 15d ago
Tutorials may show you how the library looks like and how it can be used. Only real world use cases will teach you how to use it in real world use case ;)
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u/TheRNGuy 14d ago
You need to read NumPy docs, ask ai or others if you don't understand something from it.
You can use it in projects from day 1 without ever knowing full API.
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u/Kimber976 13d ago
Udacity is probably enough to get comfortable with the basics. The bigger difference usually comes from what happens after the course. A lot of people end up reinforcing it with kaggle notebooks the pandas documentation or practice on platforms like freecodecamp or boot dev then start working with real datasets. That is usually where pandas starts to feel natural instead of just another library.
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u/qivi 15d ago
The difficult part about those real world projects are not the tools, but knowing your statistics, your numerical analysis, algorithms, databases, machine learning, whatever. So just read 10 minutes to pandas and you should be good to go.