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 explanations that align with business goals and regulatory standards, ensuring trust and compliance in financial decisions.

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. 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 risk models: train, adjust, and record predictions.
- Use SHAP and global XAI methods: uncover main factors and model patterns quickly.
- Develop fair, rule-compliant AI: spot bias, gauge effects, and apply remedies.
- Produce detailed local explanations: via SHAP, LIME, and scenario-based narratives.
- Generate XAI reports for stakeholders: including dashboards, APIs, and verifiable records.
Suggested summary
Before starting, you can change the chapters and 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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