XAI course
This course equips you with expertise in Explainable AI (XAI) for credit risk modeling. Learn to construct interpretable models, evaluate and address biases, establish monitoring systems and fairness checks, and transform SHAP analyses into concise, actionable explanations that fulfill regulatory standards and business requirements. Ideal for professionals aiming to enhance model transparency and compliance.
4 to 360h flexible workload
certificate valid in your country
What will I learn?
Gain hands-on skills to develop, interpret, and oversee credit risk models effectively. Explore data preparation, feature engineering, and preprocessing techniques. Build reliable, transparent models and apply global and local explainability methods. Assess fairness, detect biases, and implement mitigation strategies. Produce stakeholder-friendly reports, dashboards, and narratives that align with regulations and drive informed decisions.
Elevify advantages
Develop skills
- Develop explainable credit risk models through training, calibration, and thorough documentation.
- Utilize SHAP and global XAI techniques to quickly identify key factors and model patterns.
- Engineer fair and regulatory-compliant AI by identifying biases, assessing effects, and devising remedies.
- Generate detailed local explanations using SHAP, LIME, and counterfactual scenarios.
- Produce comprehensive XAI reports for stakeholders, including dashboards, APIs, and verifiable audit trails.
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 are saying
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