Foundations of Data Science

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301
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Foundations of Data Science is a comprehensive guide that introduces key concepts and techniques essential for understanding and analyzing data in the modern world. Foundational topics like statistics, probability, linear algebra, and machine learning, offering practical insights and applications in real-world data science. With a focus on both theory and implementation, it is designed for students and professionals seeking to build a solid grounding in data science principles and develop skills in data-driven problem-solving, analysis, and predictive modeling across diverse domains.

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