XAI course
Master explainable AI for credit risk modelling: construct interpretable models, assess and address bias, implement monitoring and fairness checks, and transform SHAP analyses into straightforward, regulation-compliant explanations tailored for business stakeholders and oversight needs.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain hands-on skills to develop, interpret, and oversee credit risk models reliably. Explore data, engineer features, preprocess effectively, and train accurate, understandable models. Excel in global and local explanations, fairness checks, bias identification, and remedies. 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 record risk forecasts.
- Use SHAP and global XAI methods: uncover vital factors and model patterns swiftly.
- Develop fair, regulation-compliant AI: spot bias, gauge effects, and devise fixes.
- Produce precise local explanations: apply SHAP, LIME, and counterfactual scenarios.
- Generate 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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