Machine Learning

This course starts with a short introduction to using basic machine learning methods with Python, but the emphasis of this course is the foundation of data modelling in a probabilistic framework. We discuss deep learning, convolution neural networks, generative networks, and transformers, probabilistic regression and bayesian causal networks. While there are many courses that provide recipes on how to use neural networks, the aim of this course is to get a deeper understanding of the scientific principles. This course is specifically recommended for thesis students in machine learning and students that study for a managerial level as opposed to a focus on coding instructions.