Introduction to Machine Learning (UU)

The goal of this course is to give an introduction to machine learning. We will introduce several successful methods for regression, classification, clustering, and data dimension reduction and develop the mathematical theory behind these methods, with a focus on continuous optimization theory. In the exercise sessions, the students will work on proof-style exercises, as well

Systems Analysis and Modelling

This course introduces students to systems approaches for analysing ecological and agro-ecosystems through quantitative simulation models. Students learn to formulate and specify dynamic models, evaluate model performance using statistical methods and inverse modelling, and simulate spatial processes using partial differential equations. Topics include population and nutrient dynamics, dispersal, vegetation patterning, and model calibration. Programming is

Plant Biotechnology

During the course, lectures will be given to introduce various aspects of Plant Biotechnology. The first set of lectures outlines the techniques used in Plant Biotechnology, including recent developments such as gene editing, and in the second set, specific examples of application of these techniques and the effects on science and society are provided. Societal

Perspectives on Sustainability Transitions in Agriculture

Sustainability transitions in agriculture seem inescapable. The nitrogen crisis, climate change, and diminishing biodiversity demand that governmental actors, nature conservation organizations, together with farmers, retailers, industry, academics and others develop alternatives to the dominant forms of agriculture. A protein transition, circular agriculture, nature inclusive and ecological farming are all proposed as alternatives. These alternatives also

Abiotic Stress

Environmental (abiotic) stress is the most important limiting factor in crop productivity. This master course aims to broaden the student’s horizon in abiotic-stress biology and to gain the latest insights into the molecular mechanisms by which plants perceive such stress signals, how they are transduced, and how stress signals are eventually converted into intracellular responses

Introduction to Machine Learning 2

In this course we continue with discussing machine learning models and algorithms. While the focus in Introduction to Machine Learning 1 was on programming basic models yourself, in this course we will make more use of libraries for the elementary parts and the focus will mainly be on how to combine these parts into more

Plants and Micro Organisms

De cursus bestaat uit twee delen: planten en micro-organismen. In het plantendeel worden drie thema’s behandeld. Je bestudeert fotosynthesemechanismen (C3, C4, CAM), de invloed van interne en externe milieufactoren, en de rol van fotosynthese, ademhaling en morfologie in de koolstofbalans. Daarna verdiep je je in water- en nutriëntentransport (xyleem, floëem, transpiratie, wortelstructuur, rhizosfeer, exudaten, biotische