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Nitya Narasimhan
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| solution | 3 years ago | |
| translations | 3 years ago | |
| 1-fundamentals.md | 3 years ago | |
| 2-collection.md | 3 years ago | |
| 3-privacy.md | 3 years ago | |
| 4-fairness.md | 3 years ago | |
| 5-consequences.md | 3 years ago | |
| 6-summary.md | 3 years ago | |
| README.md | 3 years ago | |
| assignment.md | 3 years ago | |
| notebook.ipynb | 3 years ago | |
| resources.md | 3 years ago | |
README.md
Data Ethics
Pre-Lecture Quiz 🎯
Pre-lecture quiz
Sketchnote 🖼
| A Visual Guide to Data Ethics by Nitya Narasimhan / (@sketchthedocs) |
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Introduction
What is ethics? What does data ethics mean, and how is it relevant to data scientists and developers in the context of big data, machine learning, and artificial intelligence? This lesson explores these ideas under the following sections:
- Fundamentals - Understand definitions, motivation and core concepts.
- Data Collection - Explore data ethics issues around data ownership, user consent and control.
- Data Privacy - Understand degrees of privacy, challenges in anonymity and leakage, and user rights.
- Algorithm Fairness - Explore consequences & harms of algorithm bias and data misrepresentation.
- Societal Consequences - Explore socio-economic issues and case studies related to data ethics.
- Summary & Resources - Wrap-up with a review of current data ethics practices and resources.
Challenge 🚀
Post-Lecture Quiz 🎯
Post-lecture quiz