The Python for Credit Risk Modeling Training Course offered by Sterling Finance Training Institute is designed to help finance professionals and data analysts develop practical expertise in using Python for credit risk evaluation and prediction. This comprehensive course focuses on real-world applications of Python in building, testing, and deploying credit risk models. Participants will explore how Python’s data analysis and machine learning libraries can enhance the efficiency and accuracy of financial decision-making processes in credit assessment.
Through hands-on exercises and industry-relevant case studies, learners will understand how to apply Logistic Regression and advanced Scoring Models to measure default risk, assess borrower behaviour, and predict repayment likelihood. The course blends financial theory with technical application, enabling participants to confidently design and implement credit risk models that comply with international risk management standards.
