Editing Human Centered Data Science (Fall 2019)
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;Human Centered Data Science: [https://myplan.uw.edu/course/#/courses/DATA512 DATA 512] - [https://www.datasciencemasters.uw.edu/program-details/courses-curriculum/course-descriptions/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [https://www.washington.edu/maps/#!/tho Thompson Hall] room 134. | ;Human Centered Data Science: [https://myplan.uw.edu/course/#/courses/DATA512 DATA 512] - [https://www.datasciencemasters.uw.edu/program-details/courses-curriculum/course-descriptions/ UW Interdisciplinary Data Science Masters Program] - Thursdays 5:00-9:50pm in [https://www.washington.edu/maps/#!/tho Thompson Hall] room 134. | ||
;Principal instructor: [[User:Jtmorgan|Jonathan T. Morgan]] | ;Principal instructor: [[User:Jtmorgan|Jonathan T. Morgan]] | ||
;Co-instructor: | ;Co-instructor: | ||
;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/1319253 Canvas]''' for announcements, file hosting, and submitting reading reflections, graded in-class assignments, and other programming and writing assignments. We will use '''[https://data512-aut19.slack.com 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/1319253 Canvas]''' for announcements, file hosting, and submitting reading reflections, graded in-class assignments, and other programming and writing assignments. We will use '''[https://data512-aut19.slack.com Slack]''' for Q&A and general discussion. | ||
;Course Description: [[Human Centered Data Science]] focuses on 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; | ;Course Description: [[Human Centered Data Science]] focuses on 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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=== Office hours === | === Office hours === | ||
* Yihan Yu: Monday 5-6:30pm ( | * Yihan Yu: Monday 5-6:30pm (location TBD) | ||
* Jonathan Morgan: Thursday 3:30 - 4:30 | * Jonathan Morgan: Thursday 3:30 - 4:30 CMU #306 ([[Community_Data_Science_Lab_(UW)|how to get there]]) | ||
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=== Lecture slides === | === Lecture slides === | ||
Slides for weekly lectures will be available in PDF form on | Slides for weekly lectures will be available in PDF form on this wiki, generally within 24 hours of each course session | ||
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* [[:File:HCDS_2018_week_1_slides.pdf|Week 1 slides]] | * [[:File:HCDS_2018_week_1_slides.pdf|Week 1 slides]] | ||
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== Schedule == | == Schedule == | ||
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Students are expected to attend class regularly. If you run into a conflict that requires you to be absent (for example, medical issues) feel free to reach out to the instructors. We will do our best to ensure that you don’t miss out, and treat your information as confidential. | Students are expected to attend class regularly. If you run into a conflict that requires you to be absent (for example, medical issues) feel free to reach out to the instructors. We will do our best to ensure that you don’t miss out, and treat your information as confidential. | ||
If you miss class session, please do not ask the professor or TA what you missed during class; check the website or ask a classmate (best bet: use Slack). Graded in-class activities cannot be made up if you miss a class session | If you miss class session, please do not ask the professor or TA what you missed during class; check the website or ask a classmate (best bet: use Slack). Graded in-class activities cannot be made up if you miss a class session. | ||
=== Grading === | === Grading === |