DAT 115 - Ethics in Data Analytics
Credits: 3
3 Lecture Hours
Description
This course introduces students to ethical models and the impact of data analytics on the evolution of societies and cultures. Students examine data handling and machine learning practices from an ethical standpoint, as well as the variations in ethical considerations across disciplines. This course prepares students to implement data analysis and machine learning in an ethical manner in their own careers.
Learning Outcomes
Upon successful completion of the course, the student will:
- Compare and contrast ethics and morals.
- Analyze applications of data analytics and machine learning in interdisciplinary environments.
- Explain algorithmic bias.
- Implement ethical decision models for data analysis.
- Assess cultural implications of data analytics.
- Describe industry accepted practices for handling sensitive identifiable data.
- Produce case studies that analyze current data analysis and machine learning issues.
Listed Topics
- Ethical models
- Comparing ethics and morals
- Cultural implementations on societal perceptions of data analysis and machine learning
- Fairness and Human Computer Interactions (HCI)
- Personal Identifiable Data (PID)
- Interpretability across disciplines
- Algorithms and social impact
- Processes for handling of sensitive data
Reference Materials
Instructor approved textbooks and materials
Students who successfully complete this course acquire general knowledge, skills and abilities that align with CCAC’s definition of an educated person. Specifically, this course fulfills these General Education Goals: - Critical Thinking & Problem Solving
- Culture Society & Citizenship
Approved By: Dr. Quintin B. Bullock Date Approved: 12/14/2020
Last Reviewed: 12/14/2020
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