Artificial Intelligence Data Fairness and Bias
- 4.9
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Course Summary
Learn about the potential biases that exist in AI data and how to address them in this course.Key Learning Points
- Understand the potential biases in AI data and their impact on decision making
- Learn techniques for addressing AI data bias
- Explore case studies and real-world examples of AI data bias
Job Positions & Salaries of people who have taken this course might have
- USA: $113,309
- India: ₹1,133,324
- Spain: €35,755
- USA: $113,309
- India: ₹1,133,324
- Spain: €35,755
- USA: $92,000
- India: ₹1,068,000
- Spain: €30,000
- USA: $113,309
- India: ₹1,133,324
- Spain: €35,755
- USA: $92,000
- India: ₹1,068,000
- Spain: €30,000
- USA: $62,453
- India: ₹405,000
- Spain: €22,000
Related Topics for further study
Learning Outcomes
- Identify potential biases in AI data
- Apply techniques for addressing AI data bias in real-world scenarios
- Understand the ethical implications of AI data bias
Prerequisites or good to have knowledge before taking this course
- Basic understanding of data analysis
- Familiarity with AI concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Data Science Ethics
- AI for Everyone
Related Education Paths
Notable People in This Field
- Co-Founder of Black in AI
- Founder of the Algorithmic Justice League
Related Books
Description
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
Outline
- Fairness and protections in machine learning
- Course Introduction Video
- Model parity: a balancing act
- Protecting groups, protecting individuals
- Imperfect modeling
- Weekly Review
- The Equality Conundrum
- COMPAS article
- Knowledge Check
- Knowledge Check
- Weekly Quiz
- Building fair models: theory and practice
- Algorithms inside of algorithms: Getting to fair
- Testing in theory: fair loan decisions
- Deploying fairness: combating bias in practice
- Adversarial Models: Word2Vec
- Weekly Review
- Unfairness visualized
- Research Paper: Debiasing Word Embeddings
- Knowledge Check
- Knowledge Check
- Weekly Quiz
- Human factors: minimizing bias in data
- Getting out of your head: bias awareness
- Building an exploratory training set
- Imperfect modeling: finding a balance
- Human Factors: Game Theory
- Weekly Review
- Full list of cognitive biases
- Monster Match
- Knowledge Check
- Knowledge Check
- Weekly Quiz
Summary of User Reviews
Discover how to identify and address data bias with Coursera's AI Data Bias course. This course has received positive reviews from users who have praised its comprehensive content and practical approach. Many users have found the course to be highly informative and engaging, with a strong focus on real-world applications.Key Aspect Users Liked About This Course
Real-world applicationsPros from User Reviews
- Comprehensive content
- Practical approach
- Informative
- Engaging
- Well-structured
Cons from User Reviews
- Some sections may be too technical for beginners
- Course material can be dense
- Limited interaction with instructors
- No hands-on exercises
Brent Summers
4.9 Raiting
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- 4.7
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