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Holistic data science education places data science in the context of real world applications, emphasizing the purpose for which data were collected, the pedigree of the data, the meaning inherent in the daa, the deploying of sustainable solutions, and the communication of key findings for addressing the original problem. As such it spends less emphasis on coding, computing, and high-end black-box algorithms. We argue that data science education must move toward a holistic curriculum, and we provide examples and reasons for this emphasis.
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Veaux et al. (2022) studied this question.
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