Our courses

Many companies have access to mountains of data and increasingly recognise the importance of turning these data into insights. This development explains the growing popularity of data analytics software such as the open-source programming environment R.

This course teaches students the analytical skills to study the possible meanings of textual and visual media representations. Through interactive lectures, students also learn concepts and methods to examine what combinations of words and/or visual elements mean in terms of a broader debate in society.

All investors – from the largest endowment funds to the smallest retail investors – share similar issues in investing: how to meet their liabilities/goals, how to decide where to invest and how much risk to take. During this course, students will learn how to think about, discuss and formulate solutions to these investment issues.

The focus of this course lies on leadership, strategy and change in a global business context. During the course, students are confronted with strategic business issues with the aim of developing business knowledge and improving leadership skills to deal with these issues in a more effective and creative way.

This course provides an introduction to modern monetary theory. During the course, students will examine the balance sheets and transactions that are relevant for understanding modern money, with a focus on the Eurozone. Furthermore, alternative explanations are brought forward that include, among others, the idea that governments spend first and collect taxes later.

During this course, students will learn about the latest developments in the financial services industry by addressing questions such as “What is the current dominant business model and how are Fintech entrants changing this business model?” and “Will Fintech offer a digital divide again or improve social inclusion?”

This course was designed for students who are interested in the aid/development sector and in logical models that can be applied to project design. During the course, students will develop their project design, monitoring and evaluation skills as well as their analytical and presentation skills.

During this course, students will look at different categories of AI project failures to better understand what went wrong. This non-technical course is aimed at future data scientists who want to take a cross-disciplinary approach to building their AI solutions that enables them to consider their projects from multiple perspectives.