Human Centered Data Science: Difference between revisions

Revision as of 23:27, 31 January 2021

Human Centered Data Science (HCDS) is a course offered by the University of Washington eScience Institute as part of the core curriculum for the Master of Science in Data Science program as DATA 512, and hosted by the Department of Human Centered Design and Engineering. The course curriculum was developed by Jonathan T. Morgan, Brock Craft, and Cecilia Aragon with contributions by Os Keyes and Brandon Martin-Anderson.

Human Centered Data Science focuses on fundamental principles of data science and its human implications, including:

research ethics
data privacy
legal considerations
algorithmic bias, transparency, fairness and accountability
data provenance, curation, preservation, and reproducibility
user experience design and research for big data
crowdwork and human computation
data communication and visualization
societal impacts of data science

Course curricula are available for the following class sessions:

Feel free to use any of the course materials hosted on this wiki! We just ask that you provide attribution by noting that you adapted or adopted materials from this course (and if possible, link back to this wiki page).

If you have questions or feedback related to the course, you are welcome to email Jonathan at jmo25 at uw dot edu.

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 == See also ==
 * [[DS4UX_(Spring_2016)|HCDE 598: Data science for UX researchers]]. A graduate level special topics class taught in 2016.
-* [[Human Data Interaction|HCDE 411: Human-data Interaction]]. A course offered as part of the [https://escience.washington.edu/education/undergraduate/ UW Undergraduate Data Science Minor]. Under development for Spring quarter 2021.
+* [[Human Data Interaction|HCDE 411: Human Data Interaction]]. A course offered as part of the [https://escience.washington.edu/education/undergraduate/ UW Undergraduate Data Science Minor]. Under development for Spring quarter 2021.