XAI course
This course equips you to master explainable AI in credit risk modelling. Build transparent models, assess and address bias, implement monitoring and fairness checks, and transform SHAP analyses into compelling, regulation-compliant explanations for business stakeholders. Perfect for ensuring trustworthy AI in finance.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
Gain hands-on skills to develop, interpret, and oversee credit risk models effectively. Cover data analysis, feature preparation, and model training for reliable, understandable predictions. Explore explainability techniques, fairness checks, bias identification, and remedies. Produce stakeholder-friendly reports, visualisations, and stories that drive decisions and comply with regulations.
Elevify advantages
Develop skills
- Develop transparent credit models: train, calibrate, and document risk forecasts.
- Use SHAP and global XAI methods: uncover vital factors and model patterns swiftly.
- Build ethical, compliant AI: spot bias, evaluate effects, and devise fixes.
- Craft precise local explanations: apply SHAP, LIME, and counterfactual scenarios.
- Produce polished XAI reports: design 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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