XAI course
Master explainable AI for credit risk modeling: develop interpretable models, assess and reduce bias, implement monitoring and fairness checks, and transform SHAP analyses into compelling, regulation-compliant explanations that align with business demands and stakeholder expectations.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain hands-on skills to construct, interpret, and oversee credit risk models reliably. Explore data, engineer features, preprocess inputs, and train precise, understandable models. Excel in global and local explanations, fairness checks, bias identification, and correction. Produce stakeholder-friendly reports, dashboards, and stories that drive decisions and comply with regulations.
Elevify advantages
Develop skills
- Build interpretable credit models: train, calibrate, and document risk forecasts.
- Use SHAP and global XAI methods: uncover vital factors and model patterns quickly.
- Ensure fair, compliant AI: spot bias, evaluate effects, and devise remedies.
- Craft precise local explanations: apply SHAP, LIME, and counterfactual scenarios.
- Produce stakeholder-approved XAI outputs: dashboards, APIs, and verifiable records.
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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