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Its robust ecosystem of libraries and frameworks tailored for Data Science, such as NumPy, Pandas, and Scikit-learn, contributes significantly to its popularity. Moreover, Python’s straightforward syntax allows DataScientists to focus on problem-solving rather than grappling with complex code.
Summary: Data Science appears challenging due to its complexity, encompassing statistics, programming, and domain knowledge. However, aspiring datascientists can overcome obstacles through continuous learning, hands-on practice, and mentorship. However, many aspiring professionals wonder: Is Data Science hard?
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