Credit Risk Modeling for Financial Institutions

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About Course

  • Tech Stack: Python (XGBoost, LightGBM), SQL, Tableau, Flask, AWS (SageMaker, RDS), Docker, Airflow
  • Objective: Build a credit risk prediction model to assess the likelihood of loan default for a financial institution. The project requires building and tuning ensemble models (XGBoost, LightGBM) and deploying the model in a Flask API with results visualized on a Tableau dashboard.
  • Skills Needed: Ensemble learning, model interpretability, API development (Flask), cloud-based model deployment (AWS), and data visualization (Tableau).

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