Eliminating Bias in AI Algorithms Course
Gain mastery in practical tools to detect, measure, and reduce bias in AI credit models. Learn essential fairness metrics, conduct data audits, implement mitigation strategies, and establish governance frameworks to create ethical, compliant, and transparent algorithms that safeguard vulnerable borrowers from unfair practices.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This course equips you with hands-on skills to audit lending datasets, identify hidden biases, and assess model performance across diverse groups. Explore crucial fairness metrics, legal requirements, and practical mitigation methods using real-world tools and tests. Develop strong monitoring, documentation, and human oversight systems to ensure automated credit decisions remain fair, transparent, and accountable throughout their lifecycle.
Elevify advantages
Develop skills
- Diagnose AI bias by auditing lending data, detecting hidden harms, and flagging risks quickly.
- Apply fairness metrics like parity, odds, and impact tests to meet legal standards.
- Mitigate bias in models by tuning data, features, and thresholds for fair credit decisions.
- Explain AI decisions through model cards, reports, and clear messages for applicants.
- Operationalise ethics with monitoring, governance, and human review processes for AI.
Suggested summary
Before starting, you can change the chapters and the 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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