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Artificial Intelligence Data Fairness and Bias
Learn how to identify and mitigate bias in AI systems, focusing on fairness in machine learning models and ethical data practices.
Course Cost
Free course
Beginner
Skill Level
3 Hours
Self-paced lessons
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Ethics in the Age of AI Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
7,692 Enrolled
English
What you'll learn
Understand fairness principles in machine learning
Identify and measure bias in AI systems
Implement techniques for building fair models
Analyze human factors in data collection and bias
Develop strategies for ethical AI deployment
Skills you'll gain
This course includes:
1.2 Hours PreRecorded video
9 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 3 modules in this course
This course explores the fundamental issues of fairness and bias in machine learning systems. Students learn about protecting groups and individuals in AI decision-making, building fair models, and minimizing human bias in data collection. The curriculum covers practical approaches to testing and deploying fair AI systems, from loan decisions to word embeddings, while addressing cognitive biases and ethical considerations in model development.
Fairness and protections in machine learning
Module 1 · 2 Hours to complete
Building fair models: theory and practice
Module 2 · 2 Hours to complete
Human factors: minimizing bias in data
Module 3 · 2 Hours to complete
Fee Structure
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Faculties
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Frequently asked Questions
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