Eliminating Bias in AI Algorithms Course
Gain practical skills to detect, measure, and reduce bias in AI credit models. Master fairness metrics, conduct data audits, implement mitigation strategies, and establish governance for ethical, compliant, and transparent algorithms that safeguard vulnerable borrowers from unfair lending practices.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Acquire hands-on skills to audit lending datasets, identify hidden biases, and assess model performance across diverse groups. Explore essential fairness metrics, legal requirements, and practical mitigation methods using real-world tools and tests. Develop strong monitoring, documentation, and human oversight processes to ensure automated credit decisions remain fair, transparent, and accountable long-term.
Elevify advantages
Develop skills
- Diagnose AI bias by auditing lending data, detecting hidden harms, and flagging risks quickly.
- Apply fairness metrics like parity, odds ratios, and impact tests to comply with legal standards.
- Mitigate bias in models by tuning data, features, and thresholds for equitable credit decisions.
- Explain AI decisions through model cards, detailed reports, and clear messages for applicants.
- Operationalise ethics with monitoring systems, governance frameworks, and human review processes.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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