Editing Human Centered Data Science (Fall 2018)
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;Human Centered Data Science: [https://sdb.admin.uw.edu/timeschd/uwnetid/sln.asp?QTRYR=AUT+2018&SLN=23353 DATA 512] - [https://www.datasciencemasters.uw.edu/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [https://www.washington.edu/classroom/ART+003 ART 003]. | ;Human Centered Data Science: [https://sdb.admin.uw.edu/timeschd/uwnetid/sln.asp?QTRYR=AUT+2018&SLN=23353 DATA 512] - [https://www.datasciencemasters.uw.edu/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [https://www.washington.edu/classroom/ART+003 ART 003]. | ||
;Principal instructor: [[User:Jtmorgan|Jonathan T. Morgan]] | ;Principal instructor: [[User:Jtmorgan|Jonathan T. Morgan]] | ||
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;Course Website: ''This wiki page is the canonical information resource for DATA512.'' All other course-related information will be linked on this page. We will use [https://canvas.uw.edu/courses/1244514 the Canvas site] for announcements, file hosting, and submitting reading reflections, graded in-class assignments, and other programming and writing assignments. We will use Slack for Q&A and general discussion. | ;Course Website: ''This wiki page is the canonical information resource for DATA512.'' All other course-related information will be linked on this page. We will use [https://canvas.uw.edu/courses/1244514 the Canvas site] for announcements, file hosting, and submitting reading reflections, graded in-class assignments, and other programming and writing assignments. We will use Slack for Q&A and general discussion. | ||
;Course Description: Fundamental principles of data science and its human implications, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness and accountability; data provenance, curation, preservation, and reproducibility; user experience design and research for big data; human computation; data communication and visualization; 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, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness and accountability; data provenance, curation, preservation, and reproducibility; user experience design and research for big data; human computation; data communication and visualization; and societal impacts of data science..<ref>https://www.washington.edu/students/crscat/data.html#data512</ref> | ||
== Overview and learning objectives == | == Overview and learning objectives == | ||
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=== Lecture slides === | === Lecture slides === | ||
Slides for weekly lectures will be available in PDF form on this wiki | Slides for weekly lectures will be available in PDF form on this wiki within 24 hours of each course session | ||
* [[:File: | <!-- | ||
* [[:File:HCDS_Week_1_slides.pdf|Week 1 slides]] | |||
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== Schedule == | == Schedule == |