LearnQuest
Artificial Intelligence Data Fairness and Bias
LearnQuest

Artificial Intelligence Data Fairness and Bias

This course is part of Ethics in the Age of AI Specialization

Taught in English

Some content may not be translated

Brent Summers

Instructor: Brent Summers

6,024 already enrolled

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

4.8

(89 reviews)

Beginner level
No prior experience required
6 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

9 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(89 reviews)

Beginner level
No prior experience required
6 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the Ethics in the Age of AI Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course

Welcome to the course! In week one, we will be discussing what fairness means in the context of machine learning and what true parity means in different scenarios

What's included

5 videos2 readings3 quizzes2 discussion prompts

This week we will take action against unfairness. Now that we have an understanding of fairness issues, how do we build models that do not violate them?

What's included

5 videos2 readings3 quizzes1 discussion prompt

This week, we will tackle the human biases that enter the data collection and attribute selection processes. The goal? Removing bias before the model is built

What's included

5 videos2 readings3 quizzes1 discussion prompt

Instructor

Instructor ratings
4.6 (28 ratings)
Brent Summers
LearnQuest
7 Courses16,346 learners

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4.8

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