Editing HCDS (Fall 2017)
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;Course Description: Fundamental principles of data science and its human implications. Data ethics, data privacy, algorithmic bias, legal frameworks, provenance and reproducibility, data curation and preservation, user experience design and research for big data, ethics of crowdwork, data communication, and societal impacts of data science.<ref>https://www.washington.edu/students/crscat/data.html#data512</ref> | ;Course Description: Fundamental principles of data science and its human implications. Data ethics, data privacy, algorithmic bias, legal frameworks, provenance and reproducibility, data curation and preservation, user experience design and research for big data, ethics of crowdwork, data communication, and societal impacts of data science.<ref>https://www.washington.edu/students/crscat/data.html#data512</ref> | ||
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== Overview and learning objectives == | == Overview and learning objectives == |