Editing Workshops and Classes

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* '''[Fall 2018]''' '''[[Human_Centered_Data_Science|DATA512: Human Centered Data Science]]''' — A core course in the [https://www.datasciencemasters.uw.edu/ UW professional Master of Science in Data Science] program covering a range of ethical and practical considerations in the practice of data science research and the design of algorithmically-driven applications taught by [[User:Jtmorgan|Jonathan T. Morgan]].  
 
* '''[Fall 2018]''' '''[[Human_Centered_Data_Science|DATA512: Human Centered Data Science]]''' — A core course in the [https://www.datasciencemasters.uw.edu/ UW professional Master of Science in Data Science] program covering a range of ethical and practical considerations in the practice of data science research and the design of algorithmically-driven applications taught by [[User:Jtmorgan|Jonathan T. Morgan]].  
 
* '''[Fall 2017]''' '''[[Innovation Communities (Spring 2017)|COM597: Innovation Communities]]''' — A [http://http://commlead.washington.edu/ UW Communication Leadership’s] elective in the “Masters in Communication in Communities and Networks” program covering using online communities to harness user innovation taught by [[User:Benjamin Mako Hill|Benjamin Mako Hill]].
 
  
 
* '''[Fall 2017]''' '''[[HCDS (Fall 2017)|DATA512: Human Centered Data Science]]''' — Fundamental principles of data science and its human implications. Data ethics; data privacy; differential privacy; algorithmic bias; legal frameworks and intellectual property; provenance and reproducibility; data curation and preservation; user experience design and usability testing for big data; ethics of crowdwork; data communication; and societal impacts of data science.
 
* '''[Fall 2017]''' '''[[HCDS (Fall 2017)|DATA512: Human Centered Data Science]]''' — Fundamental principles of data science and its human implications. Data ethics; data privacy; differential privacy; algorithmic bias; legal frameworks and intellectual property; provenance and reproducibility; data curation and preservation; user experience design and usability testing for big data; ethics of crowdwork; data communication; and societal impacts of data science.

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