u/SaiTechHub

 Projects should generally be a major focus because they demonstrate practical skills. Certifications can help show structured learning, but they shouldn't replace hands-on practice. Ideally, combine fundamentals + projects + GitHub + interview preparation, and add relevant certifications where they make sense .

I'm starting to learn Data Science with Python, but there are so many libraries that I'm not sure where to begin.

Should I focus on NumPy, Pandas, Matplotlib and Seaborn first, or are there other libraries I should learn early on?

What would you recommend based on your own experience ?