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DS-2004: Ethics and Data Policy

Your Ethics and Data Policy Tour Guides:

* Professor Jess Reia
* Emails: reia@virginia.edu
* TA: 
* Peer Mentors:
* Class Location:

Professor Office Hours:

TA Office Hours

Course Materials: Ethics and Data Policy

Subject Area and Catalog Number: Data Science, DS 2004

Year, Term and Time:

Level: Undergraduate

Credit Type: Grade (A-F)


A Little Bit About the Course

What you’ll learn along the way

...... Specific learning objectives are below (example from Foundations of ML):

Be able to describe the field of Data Science and its emerging sub-fields
Gain experience working in teams to solve Data Science problems
Gain experience communicating Data Science products
Articulate the advantages and disadvantages of selected ML approaches
Be able to select appropriate ML models given problems and data types
Understand the importance of and methods for evaluating ML models
Understand the negative outcomes associated with ML/AI bias and how they can be avoided

The course will move rather quickly and can be demanding at times. However, if we all work together to support each other you’ll be amazed how much you learn at the end of the semester!

How You’ll Know You Are Learning (Assessments)

Tech Stack (Course Delivery Tools)

Discord Invite Click

Materials That Will Aid in Your Learning (Try to use free materials):

Schedule of Topics

***NOTE: depending on student interest, the syllabus can be adjusted to accommodate additional topics

Week Theme Topics Lab Reading/Repo (Prior to Class)
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10
Week 11
Week 12
Week 13
Week 14
Week 15
Week 16

A few Policies that will Govern the Class

Grading Policies: Courses carrying a Data Science subject area use the following grading system: A, A-; B+, B, B-; C+, C, C-; D+, D, D-; F. The symbol W is used when a student officially drops a course before its completion or if the student withdraws from an academic program of the University.

Grading Scale:

  • 93-100 A
  • 90-92 A-
  • 87-89 B+
  • 83-86 B
  • 80-82 B-
  • 77-79 C+
  • 73-76 C
  • 70-72 C-
  • <70 F

University of Virginia Honor System: All work should be pledged in the spirit of the Honor System at the University of Virginia. The instructor will indicate which assignments and activities are to be done individually and which permit collaboration. The following pledge should be written out at the end of all quizzes, examinations, individual assignments, and papers: “I pledge that I have neither given nor received help on this examination (quiz, assignment, etc.)”. The pledge must be signed by the student. For more information, visit www.virginia.edu/honor.

Special Needs: The University of Virginia accommodates students with disabilities. Any SCPS student with a disability who needs accommodation (e.g., in arrangements for seating, extended time for examinations, or note-taking, etc.), should contact the Student Disability Access Center (SDAC) and provide them with appropriate medical or psychological documentation of his/her condition. Once accommodations are approved, just follow up with me concerning any logistics and implementation of accommodations. Please try to make accommodations for test-taking at least 14 business days in advance of the date of the test(s). Students with disabilities are encouraged to contact the SDAC: 434-243-5180/Voice, 434-465-6579/Video Phone, 434-243-5188/Fax. Further policies and statements are available at www.virginia.edu/studenthealth/sdac/sdac.html

Technical Support Contacts

Login/Password: scpshelpdesk@virginia.edu
UVaCollab: collab-support@virginia.edu
BbCollaborate Support: http://www.tinyurl.com/uvabbc