This intensive online training program is designed to familiarize participants with the essential machine learning tools utilized for non-linear statistical inference. It covers a range of topics, starting with multivariate discriminant analysis methods, multivariate OLS models, Ridge and LASSO regressions, decision trees, random forests, and gradient boosting algorithms, culminating in various configurations of artificial neural networks, commonly referred to as “deep learning.” The training will highlight key applications in asset liability management and customer credit scoring, beginning with traditional statistically based practices and progressing to more recent developments supported by machine learning.

The course is structured in two parts: the first half is conducted in a traditional lecture format, while the second half is case study-based, encouraging participants to engage with one another to develop optimal solutions for the presented cases. The course facilitator will serve as a moderator and catalyst, guiding participants in eliciting effective solutions. Attendees will be encouraged to critique the proposed solutions and to select the most appropriate models for each business scenario.