XAI course
Master explainable AI for credit risk modeling: construct interpretable models, assess and reduce bias, set up monitoring and fairness reviews, and convert SHAP analysis into straightforward explanations that fulfill regulatory standards and business demands, ensuring confident decision-making.

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 inputs, and train accurate, understandable models. Excel in global and local explanations, fairness checks, bias identification, and fixes. Produce stakeholder-friendly reports, dashboards, and stories that drive decisions and comply with rules.
Elevify advantages
Develop skills
- Build transparent credit models: train, adjust, and record risk forecasts.
- Use SHAP and overall XAI methods: uncover main factors and model patterns quickly.
- Develop equitable, rule-following AI: spot bias, gauge effects, and devise remedies.
- Produce precise individual explanations: via SHAP, LIME, and hypothetical scenarios.
- Generate reports ready for stakeholders: including 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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