Scoring and machine learning (R and Python)

Summary: The course provides an overview of the following Machine Learning and AI models:

1. Credit Scoring overview
2. Feature identification: PCA and FCA
3. Linear and Logistic regression
4. PCA Regression
5. Regularisation: Lasso, Ridge and Elastic Net
6. Support Vector Machine
7. Bagging and Random Forest
8. Gradient Boosting
9. Neural Networks and Deep Learning
10. Reinforcement Learning

Professor: Bertrand Hassani (CEO - Quant AI Lab)

Student assessment: Project (in Python or R)