Editing HCDS (Fall 2017)
From CommunityData
The edit can be undone. Please check the comparison below to verify that this is what you want to do, and then publish the changes below to finish undoing the edit.
Latest revision | Your text | ||
Line 1: | Line 1: | ||
<div style="font-family:Rockwell,'Courier Bold',Courier,Georgia,'Times New Roman',Times,serif; min-width:10em;"> | |||
<div style="float:left; width:100%; margin-right:2%;"> | |||
{{Link/Graphic/Main/2 | |||
|highlight color= 27666b | |||
|color=460c40 | |||
|link= | |||
|image= | |||
|text-align=left | |||
|top font-size= 1.1em | |||
|top color=FFF | |||
|line color=FFF | |||
|top text=This page is a work in progress. | |||
|bottom font-size= 1em | |||
|bottom color= FFF | |||
|bottom text=Last updated on {{REVISIONMONTH:HCDS_(Fall_2017)}}/{{REVISIONDAY2:HCDS_(Fall_2017)}}/{{REVISIONYEAR:HCDS_(Fall_2017)}} by {{REVISIONUSER:HCDS_(Fall_2017)}} | |||
|line= none | |||
}}</div></div> | |||
<div style="clear:both;"></div> | |||
;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 | ;Course Website: ''This'' page is the canonical information resource for DATA512. We will use Canvas for [https://canvas.uw.edu/courses/1174178/announcements announcements] and [https://canvas.uw.edu/courses/1174178/discussion_topics posting reading reflections], GitHub and Jupyter Hub for turning in other 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> | ||
Line 15: | Line 35: | ||
* 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 | ||
== Schedule == | == Schedule == | ||
Line 50: | Line 46: | ||
== Assignments == | == Assignments == | ||
'' | ''[[HCDS (Fall 2017)/Assignments]]'' | ||
<div class="toccolours mw-collapsible"> | |||
Graded assignments (click to expand) | |||
<div class="mw-collapsible-content"> | |||
{{:HCDS (Fall 2017)/Assignments}} | {{:HCDS (Fall 2017)/Assignments}} | ||
</div> | |||
</div> | |||
<!--== Readings == | <!--== Readings == | ||
Line 62: | Line 62: | ||
</div> | </div> | ||
</div>--> | </div>--> | ||
== Policies == | == Policies == | ||
Line 86: | Line 85: | ||
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 === |