Credit Risk Modeling and Scoring System Development

About Course
- Tools & Languages: Python, R, SQL, Tableau, SAS, Pandas, NumPy, Scikit-learn, Logistic Regression
- Objective: Develop a credit scoring system using machine learning techniques like logistic regression, decision trees, or neural networks. Build and evaluate models for predicting credit default risks using historical customer data. Implement the model in a scalable web interface and visualize insights through Tableau.
- Skills Needed: Credit risk modeling, financial data analysis, machine learning (Python, R), logistic regression, decision trees, data visualization (Tableau), SQL integration.
Student Ratings & Reviews
No Review Yet