This summer course provides a multidisciplinary perspective on games and play in contemporary culture, combining perspectives from various disciplines within the humanities, social sciences and computer sciences. It addresses the challenges but also the transformative potential of both ‘applied’ and entertainment games, and provides participants with a holistic perspective including analysis, design and validation. By combining aspects of theory and practice, the course enables participants to better understand and meaningfully implement the potential of games and play within current socio-cultural contexts.
The focus of the Mathematics Education course is: bringing participants up to date in curriculum development and research in the field of mathematics education, and refreshing and deepening the knowledge of meaningful and relevant mathematics education. Topics will include: curriculum development, revealing and building on talents of students, task design, classroom experiments and lesson study, contexts and tools for modeling and inquiry-based learning, assessment, and the use of technology for teaching and learning mathematics.
Our world has an abundance of so-called complex systems. These are typically large collections of connected elements that influence each other. In this online course, we combine examples across physics, the life sciences, socio-economic sciences and humanities with an introduction to basic mathematical tools to learn a complex systems way of thinking. The main aim is to show students how complex systems science is applied by Utrecht University researchers to challenging societal problems.
Typed functional programming languages allow for the rapid development of robust programs. This course explores some of the more advanced language features of Haskell, a state of the art functional programming language, together with some of its theoretical background. The course aims to teach not only the more advanced Haskell features, such as GADTs or type families, but also the underlying theory. Besides the lectures, there are numerous supervised lab sessions to help you come to grips with the material covered in class.
This course is a hands-on course on GIS: 2 weeks of practicals in the GIS Lab of the faculty of Geosciences. The following topics will be covered: Working with ArcGIS Pro and Spatial Analyst, Modelbuilder and Python, automatic DEM extraction of stereo aerial photographs using Erdas Imagine eATE and Agisoft, Mobile GIS / GPS data collection, local/global datasets and datatypes, and poster making.
How do meteorologists forecast the weather and climate? Is there a way to predict the profit from a wind farm? These are some of the questions modern science addresses by using data assimilation. Many research institutes and companies (e.g. KNMI, Shell, US-NCAR or UK MetOffice) develop and employ data assimilation and the demand for trained personnel is constantly growing. The school will describe the theoretical foundation of data assimilation together with numerical tutorials, all the way to state-of-the-art methods, including modern machine learning approaches and their combination with data assimilation.