English

Machine learning is a fast-growing field and plays a central role in the era of AI and big data with many applications in prediction and data analysis. In particular, optimization formulations and algorithms are key to analysis and design of efficient methods in machine learning problems. This course focuses on the optimization models arising from various machine learning problems and introduce efficient algorithms for solving these models. The course covers basic convex analysis, model formulation, and fundamental (stochastic) first-order methods, supplemented with recent developments in the related literature.

This course introduces contemporary issues in democratic theory and philosophy and public policy. It draws on political and moral philosophy as well as philosophy of law in order to examine the philosophical underpinnings of contemporary political debates over civil rights and liberties, democratic institutions and procedures, inequality and disadvantage and human rights. It combines the study of contemporary philosophy with analysis of particular cases, through a mixture of academic articles, newspaper articles, public policy reports and recently published works by distinguished academics.

The prime purpose of the Advanced GIS course is to widen your knowledge and skills in the practical – foremost analytical – application of Geographical Information Systems using raster models and spatial network models. As a consequence, a substantial part of the course consists of practical assignments in which participants train their skills in GIS analysis. At the same time, start your own analytical GIS project on planning a new road in Friesland. The practical assignments are partly integrated with the project. Work together with one or two fellow students, directly applying your new skills in the project. The project is concluded with two reports on progress and outcomes (maps, charts, etc.).

This course explores American foreign policy at the broadest level of analysis – the level known as grand strategy. The course showcases the main theoretical perspectives that inform the study of grand strategy and applies them to historical and contemporary cases of American statecraft. In this connection, students assess the relevance of the U.S. experience for theorizing about power politics and the implications of alternative theories for thinking critically about American international behavior. Emphasis is placed on the debates and controversies that animate the study of grand strategy, as well as of the unique challenges posed by making foreign policy in the American political, economic, and cultural context.

Machine learning is concerned with algorithms that process relevant data and then perform some task. Often, performance of machine learning algorithms is measured statistically, and the algorithms themselves are heavily influenced by statistical ideas. For example, after observing several (x,y) pairs an algorithm may be able to predict with high accuracy the corresponding value of y for an unseen x. When the data is complex and/or high-dimensional, a number of statistical and algorithmic issues arise: a sufficiently rich class of statistical models must be used effectively and irrelevant data should be identified and then discarded. Students understand the statistical approach to analyzing data, and how it can be used to effectively perform tasks under appropriate assumptions. This enables students to formulate various real-life problems as statistical learning tasks and use common techniques to develop solutions.

This course will analyze media content in several different medium, such as photographs, newspaper articles, advertisements, tv shows, movies, new media, public relations, fake news and digital literacy. It helps develop an understanding of how this media content influences people in everyday life, social development and political economic changes. It defines Information Literacy are the skill set needed to locate and recognize quality information resources to help students utilize the information in a responsible and effective way and defines Media Literacy as a way of thinking about the media and a way of deconstructing and understanding media messages to gain more control over them. Other topics include Resource Literacy, Social-Structural Literacy, Research Literacy, and Publishing Literacy.

In this course, students study autism spectrum disorder, a neurodevelopmental condition, across all stages of the lifespan – from early childhood into old age. The course focuses on cognition, while contextualizing the condition at different stages of development. Students explore areas in childhood and adolescence, including memory, language, learning, the "self," mental health, and transgender issues. Students also examine adulthood topics including Bayesian theories of perception, maternal autism, memory, sensory, and emotional processing. The course finishes with addressing some of the consequences of ageing in autism.

In the period from roughly the late fifteenth to the mid-nineteenth century, developments took place that would form the basis of the world as we know it today. States took on recognizable forms, merchants looked for new markets within and outside Europe, and the Reformation, the Scientific Revolution and the Enlightenment resulted in new insights and world views. The Atlantic Revolutions and the Industrial Revolutions from the end of the 18th century would permanently change the world politically and economically. The (Early)modern History course focuses on three, often closely related, thematic areas: political, socio-economic, and cultural and religious developments. The course answers the following questions: how did the French Revolution change the political landscape of Europe? What was the role of Europeans in globalization? How did the Reformation and state formation become entwined?

This course provides a continuation of the study of medical statistics, with emphasis on more advanced topics in epidemiological methods and the design and analysis of clinical trials. Students learn how to model survival data using parametric regression models; to develop and validate a risk prediction model; to analyze clustered data using a regression model; to design and analyze a cross-over trial, cluster randomized trial, equivalence trial, and early phase trial; to understand the issues concerning interim analyses and missing data; and to carry out a meta-analysis.

This course examines quality of life through the study of leisure, life, and happiness in contemporary society. Students explore classical and contemporary theories, research findings, and everyday experiences to understand how leisure contributes to individual well-being and life satisfaction. While the primary focus is on personal meaning-making, the course also introduces a life-course perspective, encouraging students to consider how leisure, work, and happiness may change across different stages of life. Through lectures, discussions, presentations, and reflective assignments, students develop a deeper understanding of leisure as a key component of a meaningful and balanced life. Active participation and several outside assignments are required.