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Aspiring data scientists must master linear algebra, calculus, probability, and statistics before writing code. These four disciplines separate those who run pre-built models from those who understand why models work. Mathematical intuition speeds debugging, improves algorithm selection, and enables creative problem-solving that libraries cannot replace.
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