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@ -13,11 +13,11 @@
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This lesson dives into a critical topic for the modern data scientist: _data ethics_.
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In this lesson we'll cover:
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1. _[Fundamentals]()_ - Principles & History
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1. _[Fundamentals](#1-fundamentals)_ - Principles & History
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2. _[Data Collection](#2-data-collection)_ - Ownership & Consent
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3. _[Data Privacy](#2-data-privacy)_ - Protection & Anonymity
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4. _[Fairness](#4-fairness)_ - Algorithm Bias &
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5. _[Tools](5-tools)_ - Checklists & Frameworks
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3. _[Data Privacy](#3-data-privacy)_ - Protection & Anonymity
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4. _[Algorithms & Fairness](#4-algorithms-and-fairness)_ - Unfairness, Harms & Bias
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5. _[Tools & Frameworks](5-tools-and-frameworks)_ - Codes, Checklists & Frameworks
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6. _[Summary](6-summary)_ - Related Work
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<br/>
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@ -56,7 +56,7 @@ In this lesson we'll cover:
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<br/>
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## 4. Algorithms Fairness
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## 4. Algorithms and Fairness
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@ -67,7 +67,7 @@ In this lesson we'll cover:
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<br/>
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## 5. Tools
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## 5. Tools and Frameworks
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