Regression modelling is a fundamental tool of statistics, because it describes how the law of a random variable of interest may depend on other variables. This course aims to familiarize students with linear models and some of their extensions, which lie a ...
Hands-on introduction to data science and machine learning. We explore recommender systems, generative AI, chatbots, graphs, as well as regression, classification, clustering, dimensionality reduction, text analytics, neural networks. The course consists o ...
This class explores key climate questions through data. Students will learn to collect, clean, and analyze data, apply causal methods using Python, and communicate insights clearly. With a focus on sustainability, the course builds skills to avoid pitfalls ...
Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
This course introduces the principles of model identification for non-linear dynamic systems, and provides a set of possible solution methods that are thoroughly characterized in terms of modelling assumptions and uncertainty levels. ...
This class provides a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition and cleaning, regression, classification, clustering, neural networks, and visualization. The course consists of lectures and ...