DATA414
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Ethics of Models, Metrics, Algorithms, and Data
Subject
DATA - Data Science
Description
Ethical frameworks pertaining to data science. Algorithmic fairness and bias. Explainable results in machine learning and artificial intelligence. Privacy and data governance for large datasets. Human implications of data science in Indigenous and underserved communities.
Prerequisite(s): Data Science 221.
Antirequisite(s): Credit for Data Science 414 and Philosophy 314 will not be allowed.
Prerequisite(s): Data Science 221.
Antirequisite(s): Credit for Data Science 414 and Philosophy 314 will not be allowed.
Signature Learning
Entrepreneurial Thinking, Research & Creative Scholarship
Course Attributes
Fee Rate Group(Domestic) - A, Fee Rate Group(International) -A, GFC Hours (3-2T), RCS Related, Entrepreneurial Thinking - Related, Research & Creative Scholarship - Related
Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.
Component
LEC
Component
TUT
Units
3
Repeat for Credit
No
Subject code
DATA