Editing HCDS (Fall 2017)
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;Human Centered Data Science: [https://sdb.admin.uw.edu/timeschd/uwnetid/sln.asp?QTRYR=AUT+2017&SLN=23273 DATA 512] - [https://www.datasciencemasters.uw.edu/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [http://www.washington.edu/maps/#!/den Denny Hall] 112. | ;Human Centered Data Science: [https://sdb.admin.uw.edu/timeschd/uwnetid/sln.asp?QTRYR=AUT+2017&SLN=23273 DATA 512] - [https://www.datasciencemasters.uw.edu/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [http://www.washington.edu/maps/#!/den Denny Hall] 112. | ||
; | ;Instructor: [http://jtmorgan.net Jonathan T. Morgan] | ||
; | ;TA: Oliver Keyes | ||
;Course Website: ''This'' page is the canonical information resource for DATA512. We will use [https://canvas.uw.edu/courses/1174178 the Canvas site] for announcements, file hosting, and submitting reading reflections and graded in-class assignments. We will use Jupyter Hub ( | ;Course Website: ''This'' page is the canonical information resource for DATA512. We will use [https://canvas.uw.edu/courses/1174178 the Canvas site] for announcements, file hosting, and submitting reading reflections and graded in-class assignments. We will use Jupyter Hub (link coming soon!) for turning in other programming and writing assignments, and Slack for Q&A and general discussion. All other course-related information will be linked on this page. | ||
;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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* Discuss and evaluate ethical, social and legal trade-offs of different data analysis, testing, curation, and sharing methods | * Discuss and evaluate ethical, social and legal trade-offs of different data analysis, testing, curation, and sharing methods | ||
== Office hours == | |||
* Oliver: Monday (10-12am) and Wednesday (4-6pm), Sieg 422, and by request. | |||
* Jonathan: as needed (virtual) | |||
* Oliver: Monday ( | |||
* Jonathan: | |||
== Schedule == | == Schedule == | ||
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== Policies == | == Policies == | ||
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Active participation in class activities is one of the requirements of the course. You are expected to engage in group activities, class discussions, interactions with your peers, and constructive critiques as part of the course work. This will help you hone your communication and other professional skills. Correspondingly, working in groups or on teams is an essential part of all data science disciplines. As part of this course, you will be asked to provide feedback of your peers' work. | Active participation in class activities is one of the requirements of the course. You are expected to engage in group activities, class discussions, interactions with your peers, and constructive critiques as part of the course work. This will help you hone your communication and other professional skills. Correspondingly, working in groups or on teams is an essential part of all data science disciplines. As part of this course, you will be asked to provide feedback of your peers' work. | ||
=== Assignments and coursework === | === Assignments and coursework === |