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Being Agile in a Data Science Project

Lecture Notes in Business Information Processing (2024) 489 LNBIP 51-59
DOI: 10.1007/978-3-031-48550-3_6
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Abstract

Applying agile practices in data science requires adaptations. This paper describes challenges and lessons learned in two applied machine learning projects developed in the XP Lab course at University of São Paulo in Brazil. It compiles six suggestions for educators and practitioners who want to bring agility to their data science initiatives.

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Cordeiro, R., Alves, I., Alves, S., & Goldman, A. (2024). Being Agile in a Data Science Project. In Lecture Notes in Business Information Processing (Vol. 489 LNBIP, pp. 51–59). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-48550-3_6

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