XAI course
Master explainable AI for credit risk modelling. Build transparent models, assess and reduce bias, set up monitoring and fairness reviews, and convert SHAP analysis into simple explanations that align with business goals and regulatory standards. Learn practical tools to make AI trustworthy and compliant in real-world finance.

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 effectively. Explore data, engineer features, preprocess inputs, and build reliable, understandable models. Dive into global and local explanations, fairness checks, bias spotting, and fixes. Produce straightforward reports, dashboards, and stories that meet stakeholder demands and regulations.
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 patterns quickly.
- Develop fair and rule-compliant AI: spot bias, gauge effects, and apply fixes.
- Produce detailed local explanations: with SHAP, LIME, and what-if scenarios.
- Prepare XAI reports for stakeholders: including dashboards, APIs, and full audit 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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