Explainable AI Course
This course teaches practical Explainable AI techniques for building transparent loan and credit-risk models, focusing on fairness, interpretability, and production deployment.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This short, practical Explainable AI Course shows you how to build transparent loan and credit-risk models from real datasets, define targets, and engineer features for reliable predictions. You will apply global and local explainability methods, design clear approval and rejection reasons, address fairness and bias, and deploy an explainability-first system that is compliant, auditable, and ready for production use.
Elevify advantages
Develop skills
- Build fair loan models: detect bias, apply metrics, and ship compliant fixes fast.
- Explain models globally: use feature importance and PDPs for clear loan insights.
- Deliver local decisions: apply SHAP, LIME, and counterfactuals in plain english.
- Design XAI-first systems: integrate explanations into APIs, UI, and monitoring.
- Engineer credit data: craft calibrated, interpretable models for risk scoring.
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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