XAI course
Master explainable AI for credit risk modelling. Build transparent models, assess and reduce bias, set up monitoring and fairness reviews, and transform SHAP analysis into straightforward explanations that align with business goals and regulatory standards. Perfect for practical, compliant AI deployment.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain hands-on skills to develop, interpret, and track credit risk models reliably. Cover data analysis, feature preparation, and model training for clear, accurate predictions. Dive into explainability techniques, 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 risk models: train, adjust, and record predictions.
- Use SHAP and overall XAI methods: spot main factors and model patterns quickly.
- Develop fair, rule-compliant AI: identify bias, gauge effects, and apply fixes.
- Craft precise local explanations: via SHAP, LIME, and scenario-based narratives.
- Produce XAI reports for stakeholders: including dashboards, APIs, and full 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 say
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