Modelling and Problem Solving

The course covers major (combinatorial) solving approaches, namely constraint programming, integer programming, boolean satisfiability, dynamic programming and decision diagrams, and local search. The course focuses on modelling practical problems, expressing them in the surveyed paradigms; algorithms for solving such problems are covered in the follow-up “Constraint Solving” course. The topic of genetic algorithms is reserved

Sustainable food systems

Our current globalized food system is often at the core of the pressure on sustainable development goals such as life on land, life below water, and water and sanitation, while failing to meet goals such as zero hunger and no poverty. Understanding the causes of the current unsustainable situation and developing solutions to stimulate a

Applied Machine Learning

Machine learning is marking a revolution in the world. From an academic research topic, over the last decade it has shift to a major paradigm used in many companies for a wide range of services. From deleting SPAM mail from your inbox to ranking the Google search results, and from defining your Facebook stream to

Deep Learning 1

Deep learning is primarily a study of multi-layered neural networks, spanning over a great range of model architectures. We cover the basic following content in theory and in practice. We adapt the content, especially in the last lectures, based on the latest advances: Introduction to deep learning. A brief introduction of deep learning. History, recent

Ziekte en Afweer van Plant en Dier

In dit blok gaan we in op de vragen: Wat zijn (planten)ziekten en plagen? Hoe werkt het immuunsysteem van planten en dieren zoals de mens? De behandelde thema’s zijn: Verschillende klassen van ziekteverwekkers (schimmels, oömyceten, bacteriën, parasitaire planten, nematoden, virussen, en herbivoren), De mechanismen waarmee deze organismen planten binnen dringen, de plantenafweer omzeilen en/of onderdrukken,