Programme structure
The EPA curriculum has three interwoven learning lines, each one designed to develop distinct yet complementary skill sets. Modeling and Simulation Line prepares you to become a skilled analyst, teaching you to analyze, model, simulate complex, multi-actor challenges. Policy and Politics Line adds to the impact of your analysis in a policy context, as it focuses on decision-making as an evolving process. You will navigate the diverse economic, ethical, and political dimensions involved in shaping policies. You will gain insight into how stakeholder interests and social values impact real-world outcomes. Integration Line brings together the analytical and policy skills from the first two lines, applying them in a practical, interdisciplinary context. Through case studies and real-world projects, you will bridge the gap between technical analysis and strategic decision-making, gaining a holistic view of how solutions are implemented and evaluated.
These three lines reflect EPA’s interdisciplinary approach. In your first year (based in The Hague), you will establish a strong foundation across all lines. The second year expands this foundation, with courses held in both The Hague and Delft, where you will further apply and deepen your expertise.
Courses in Learning lines
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This course focuses on developing a solid basis in the political aspects of decision theory, such as understanding the institutional context in which decision-making takes place and applying various models of decision-making to real-life cases. It ‘annotates’ and ‘criticizes’ the rational perspective of the advanced modeling courses running parallel to it in the modeling line.
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The goal of this course is to teach the students how to identify, analyze and classify the societal ethical and environmental impacts of large-scale projects. Four major assessment and evaluation methods will be discussed, i.e. Environmental Impact Assessment, Social Impact Assessment, Risk Analysis and Societal Cost Benefit Analysis.
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This course introduces students to the basic macro-economic concepts and macro-analysis. The major competing macro-economic theories will be reviewed and used to assess the policy impacts of fiscal, monetary, trade and (energy) technology policies. Special attention will be paid to static and dynamic computable general equilibrium (CGE) models, which are used for policy analysis by the World Bank, the IMF, the OECD and the World Trade Organization (WTO).
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This course offers an introduction to programming concepts and libraries in Python that are essential for data science and for running large scale simulation models. The course provides a mix of theory and hands-on skills which are practiced using lab sessions.
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This course will train students to gather, merge and clean data from multiple sources. We will focus on urban areas with a spatial lens to gain valuable insights into the reality of multiple societal problems like climate change, energy transition, and inequalities. Data science will help us understand and estimate multiple implications of solutions and communicate results to a broad audience effectively.
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The overarching objective of this course is to deepen the knowledge of the students with respect to System Dynamics. To this end, the course discusses key research topics within the SD community. Specific attention will be given to when and why to use System Dynamics, how to use data in the development and testing of SD models, state of the art approaches to model validation, and formal model analysis, and the use of SD models in simulation gaming.
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The objective of this course is to provide students with a selection of topics that are state-of-the-art in simulation. The course will focus on the theoretical foundation of (potentially large-scale) data-driven simulation, as well as the corresponding methods and techniques.
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This course lays the foundation for the program. It teaches both systems thinking and decision-making processes. At the same time it teaches you to reflect on the role and position of the policy analyst for policy interventions.
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This course provides students with a range of models and analytical lenses to understand actor interactions in a strategic decision-making or policy-making environment. A generic framework for such analysis is offered, while introducing core concepts used in actor modeling.
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This course focuses on theories about group behaviour, as many models attempt to assume these interactions. It also introduces students to theories on communication, diversity and inclusiveness, and group dynamics, driving students to explore solutions for grand challenges while working in international interdisciplinary teams.
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This course aims to build a bridge between the modeling approaches and the theories on decision making. The course will, on the one hand, build on the recent work on model-based decision support for decision making under deep uncertainty. On the other hand, this course will cover recent work on contested knowledge claims, co-production of science-based policy, and deliberative policy analysis.
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In this second year course, you will apply the knowledge you obtained in the first year of the EPA Program to a (partial) solution for a specific societal challenge. You will work on one of the cases defined by an external client, such as the Ministry of the Interior, the Municipality of the Hague, etc. The projects address a real-life problem, i.e. a societal challenge, and allow you to work on a real consultancy job with a real customer organization.
Specialisations
After the first year is completed, in the second year you can choose a specialisation to deepen your expertise in a specific area.
