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 (see Canvas for link) 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 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 (see Canvas for link) 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. | ||
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== Course resources == | == Course resources == | ||
=== Office hours === | === Office hours === | ||
* Oliver: Monday ( | * Oliver: Monday (10-12am) and TBD, Sieg 422, and by request. | ||
* Jonathan: Google Hangout, by request | * Jonathan: Google Hangout, by request | ||
=== Jupyter Hub === | === Jupyter Hub === | ||
The course will use a [http://jupyter.org/ Jupyter Hub] provided by [http://westbigdatahub.org/ West Big Data Hub] and administered by [https://bids.berkeley.edu/people/yuvi-panda Yuvi Panda] at the Berkeley Institute for Data Science. Students use Jupyter notebooks for in-class and homework assignments that involve a combination of programming, analysis, documentation, and reflection. Allowing students to work in a shared, online environment reinforces best practices around open research such as transparency, iteration, and reproducibility. It also helps teaches them how to tell the story of their research using multiple media (code, data, prose, and visualizations), making it more accessible and impactful for a wider variety of audiences. | The course will use a [http://jupyter.org/ Jupyter Hub] provided by [http://westbigdatahub.org/ West Big Data Hub] and administered by [https://bids.berkeley.edu/people/yuvi-panda Yuvi Panda] at the Berkeley Institute for Data Science. Students use Jupyter notebooks for in-class and homework assignments that involve a combination of programming, analysis, documentation, and reflection. Allowing students to work in a shared, online environment reinforces best practices around open research such as transparency, iteration, and reproducibility. It also helps teaches them how to tell the story of their research using multiple media (code, data, prose, and visualizations), making it more accessible and impactful for a wider variety of audiences. | ||
== Schedule == | == Schedule == | ||
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== Policies == | == Policies == | ||
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The following grading scheme will be used to evaluate each of the 6 individual assignments (not reading reflections or graded in-class activities). | The following grading scheme will be used to evaluate each of the 6 individual assignments (not reading reflections or graded in-class activities). | ||
;81-100% - | ;81-100% - Above and beyond: The student demonstrated novelty or insight beyond the specific requirements of the assignment. | ||
;61-80% - Competent: The student competently and confidently addressed requirements to a good standard. | ;61-80% - Competent and confident: The student competently and confidently addressed requirements to a good standard. | ||
;41-60% - Acceptable: The student met the absolute minimum requirements for the assignment. | ;41-60% - Acceptable: The student met the absolute minimum requirements for the assignment. |