Bioinformatics and Genomics
In this course, attention is paid to understanding and working with large amounts of data as has been obtained in recent years with genetic and molecular research. These technological developments require new skills and concepts to be able to understand and conduct life science research. Successively work with mutations and sequencing data will be used.
Fundamentals of Data Science
Data science is a dynamic and fast-growing interdisciplinary research field that, across science, industry, and government, is altering how people understand the world and make decisions. Not surprisingly, the demand for data science skills is on the rise. This course will cover key principles and tools of data science. In particular, the course will cover
Programming in Python
Programming plays an important role in many domains. In business and science writing or adapting computer programs to process, analyse and visualize data in a suitable format has become common practice. This course aims to help students to understand the underlying principles of programming and equip them with basic skills to create computer programs. The
Plant-Microbe Interactions
Plant-microbe interactions will be introduced in a general lecture, highlighting recent developments and the importance of the reviewing process. For a set of recent manuscripts the students will act as reviewers and editors following the format provided by high standard international journals. Editor decisions will be presented and discussed.
Introduction to Bioinformatics
Over the last decades, a number of technologies to study DNA, RNA, proteins, metabolites and their interactions has been developed. To understand life at the molecular level, they have been applied in numerous biological and biomedical experiments. Much of the resulting data, as well as the knowledge gained in these experiments, are freely available for
Big Data Processing
The term “Big Data” describes datasets that are either too big or change too fast or both to be processed on a single computer. Big Data Processing provides an introduction to systems and algorithms used to process Big Data. The main focus of the course is programming and engineering big data systems; initially, the course
Data Analysis for Biosystems Engineering
The following topics will be addressed in the course: linear regression and multiple linear regression, including model formulation, meaning of model parameters, checking model assumptions and prediction; data transformation; experimental design, including completely randomized design, block design and factorial design, and calculating the required sample size to obtain a certain precision; analysis of variance and
Biotechnology and the Societal Challenge
This course explores how biotechnology can address key societal challenges identified by the European Union. These include health and demographic change, food security and sustainable agriculture, clean energy, and climate action. Students are introduced to plant and microbial biotechnology, ethical considerations, and patent systems. As part of the course, students formulate their own biotechnology-based solutions
Agroecology
The course focuses on agroecological principles to analyse and design sustainable and productive farming systems. Agroecological principles include: Recycling and efficiency; Living Soils; Biodiversity; Ecosystem services and multi-functionality; Resilience; Fair Markets; Culture & spirituality; Youth & Women; Adequate Policies & governance; Knowledge co-creation and collaboration. Students will explore how agroecological farming systems are developed across
Germplasm and Seed Technology
This course introduces students to a number of important aspects of plant breeding, such as the process of domestication, germplasm development and the importance of gene banks. Also, important practical aspects on bringing a cultivar to the market are discussed, such as breeders’ rights and patents, and the design of seed and plant production programs.