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This course introduces the general method and use of cost-benefit analysis with a particular emphasis on applications to resource and environmental economics. The course therefore deals with many crucial aspects of environmental cost-benefit analysis to provide the necessary background to assess the validity of practical environmental cost-benefit analyses, as well as to formulate how current guidelines can be improved based on the latest economic research. The course consists of a lecture block that provides an overview and introduces students to key concepts. Assessment is based on a presentation and written assignment on a topic of the student’s choosing.
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This course focuses on presenting theories and empirical data regarding global social inequality. Accounting for a wide range of sociological theories of inequality, it analyzes various theories about what creates differences in wealth between individuals and between different regions in the world. The course investigates inequality in relation to gender, ethnicity, elites, power, health, social mobility, and economy.
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COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
This course connects the microscopic description of chemical reactions with macroscopic measurable quantities and explores the processes responsible for chemical changes: molecular collisions, elementary reactions, surface phenomena, catalysis, absorption isotherms, theory of the activated complex, and diffusion controlled reactions.
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COURSE DETAIL
COURSE DETAIL
This course introduces "open" tools and methods for processing and visualizing data types such as structured data, text data, and temporal data. It discusses the opportunities and challenges in relation to working with large amounts of data, including ethical conditions regarding data acquisition, storage, aggregation, publication, and use. The course applies theories and concepts to define and analyze issues relating to large amounts of data. Students learn to develop solutions for retrieval and sorting structured and unstructured data, as well as process and represent data visually. The course largely involves hands-on cases working with relevant data sets, including an introduction to the language Python and the use of Python for data analysis such as text mining and sentiment analysis. It also introduces the principles behind FAIR data and explores ethical issues when working with open data.
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