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In this course you will learn modern statistical computing as viewed in data science through implementations in popular computing platforms such as R and Python. It covers the following topics: The R and Python environment: R packages…

Machine learning refers to statistical model predictions that that improve through experience; as new data arrive, the model learns and adapts. For instance, the price that the supermarket can charge for advertisements depends critically…

This course covers advanced machine learning methods that are relevant for applications in business and economics, and is intended as a continuation of STAN51 Machine Learning from a Regression Perspective. Some of the topics covered…

The course covers matrices and multivariate normal distribution singular value decomposition and its geometric interpretation principal component analysis including its functional formulation factor analysis cluster analysis …

The course consists of supervised study and group discussion of selected texts, independent study and oral presentation of selected primary texts and a detailed outline of the projected master’s thesis.