Professional Certificate in Machine Learning Fairness in Practice
-- viewing nowThe Professional Certificate in Machine Learning Fairness in Practice is a timely and essential course that addresses the critical issue of fairness in AI and machine learning models. This program is designed to equip learners with the practical skills to identify, measure, and mitigate bias in AI systems, promoting ethical and unbiased decision-making.
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Course Details
• Introduction to Machine Learning Fairness
• Bias in Machine Learning
• Types of Bias: Selection, Measurement, and Algorithmic Bias
• Quantifying Fairness in Machine Learning Models
• Regulations and Legal Considerations for Fair Machine Learning
• Techniques for Improving Machine Learning Fairness: Pre-processing, In-processing, and Post-processing
• Evaluation Metrics for Fair Machine Learning
• Real-world Examples of Machine Learning Fairness
• Best Practices for Developing Fair Machine Learning Models
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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