XAI course
Master explainable AI for credit risk modelling: construct interpretable models, assess and reduce bias, set up monitoring and fairness reviews, and convert SHAP analysis into straightforward, stakeholder-approved explanations that fulfil regulatory demands and business goals. This course equips you with practical tools for transparent, fair AI in finance.

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 confidently. Explore data, engineer features, preprocess effectively, and train reliable, understandable models. Excel in global and local explanations, fairness checks, bias spotting, and fixes. Produce straightforward reports, dashboards, and stories that meet stakeholder needs, aid choices, and comply with rules.
Elevify advantages
Develop skills
- Build transparent credit risk models: train, adjust, and record predictions properly.
- Use SHAP and overall XAI methods: uncover main factors and model actions quickly.
- Develop fair, rule-compliant AI: spot bias, gauge effects, and apply remedies.
- Produce detailed local explanations: via SHAP, LIME, and what-if scenarios.
- Prepare XAI reports for stakeholders: including dashboards, APIs, and full audit records.
Suggested summary
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