51ÖØ¿ÚÁÔÆæ

This increase of sustainability discourses in the daily practices of society might contribute to shifting the current unsustainable trajectory. For this course, popular culture is defined as the entirety of attitudes, ideas…

The course constitutes a 3rd term elective (non-compulsory) course at LUMES, 51ÖØ¿ÚÁÔÆæ Master's Programme in Environmental Studies and Sustainability Science.

The course turns to active musicians and music teachers and students at a Music Academy or the equivalent. The course contains advanced development and practise methods regarding tone formation, articulation, timbres and fingering…

The course includes advanced development and practice of tone formation, articulation, timbre, finger technique, special grips, and Sons filés. The students will be introduced to the solo piccolo repertoire ranging from Vivaldi to…

Students will learn advanced development and practice of tone formation, articulation, timbre, finger technique, special grips, and solo repertoire for the contrabassoon. The teaching consists of a mix between group lessons and individual…

Students will learn advanced development and practice of tone formation, articulation, timbre, finger technique, special grips, and solo repertoire for the bass clarinet. The teaching consists of a mix between group lessons and individual…

‘Just practise enough and everything will be fine!’ Is it really that simple? Why does it feel so difficult and discouraging at times? This course is designed for students at music academies, but also for active musicians and music…

The course presents modern microeconomic theory and a set of applications. The applications considered include: The theory of economic decision making under risk and uncertainty, including the important notions of risk aversion and…

The first part of this course will discuss how rational people should make simple decisions and form empirical judgments. This part also discusses the systematic ways in which real human beings deviate from these models in practice. A…

This course gives the basis that is needed to enable students to empirically analyse economic data without making unrealistic assumptions. Modern econometric techniques are treated, and at the same time considerable emphasis is placed on…

The content of the course is the following topics: • Elementary set theory (set inclusion, union, intersection), • Elementary number theory (natural numbers, rational numbers, real numbers), • Elementary functions …

This course covers modern econometric tools and empirical strategies used by economists and demographers for the analysis of cross-sectional and panel micro-data. The course teaches the econometric theory behind these techniques but also…

The course gives an introduction to basic concepts within time series analysis. The univariate analysis of time series in this course is based upon ARMA/ARIMA and ARCH-/GARCH models. Multivariate time series analysis is based on VAR models…

The course deals primarily with the short run, i.e. business cycle phenomena and stabilization policy. In addition, the determinants of long-run inflation and unemployment are studied. The course begins with consumption and investment…

The course focuses on macroeconomic issues that arise when studying and analysing open economies. The content of the course is focused on understanding how international flows of goods, services and capital affect open economies, and how…

These areas usually include individual health related behaviour, the physician-patient relationship, health insurance, competition in the hospital industry, innovation and diffusion of medical technology, equity in theory and practice,…

The course covers and discusses recent advances in Labour Economics, with an emphasis on empirical applications. Each lecture focuses on a specific topic. The course starts by discussing theories of labour supply and demand, and proceeds…

The course deals with both regional and multilateral economic integration, and the institutional and economic context within which they take place. Examples of issues covered include the current challenges faced by the World Trade…

The course deals with the mechanisms behind and the effects of international trade. The course uses an advanced treatment in terms of topics and methodology, qualifying the student to carry out advanced analyses and the study of issues…

The course aims at deepening the student's theoretical and methodological knowledge of development economics. The point of departure is that economies are low-income because of a lack of economic growth. This in turn depends on low…

The course contains the following building blocks: Investment decision under certainty: the risk free rate and Fisher-separability Risk aversion and expected utility Arrow-Debreu securities Portfolio theory Market equilibrium:…

The course begins with a brief discussion of estimation methods that can be used to analyse financial models, such as Least Square (LS), Maximum Likelihood (ML) and Generalised Method of Moment (GMM). This is followed by a description of…

The objective of this course is to give the students an understanding and hands-on knowledge of fundamental methods within financial risk management. The course deals with two main topics: measurement and management of market risk and…

The course primarily treats issues related to economic growth using advanced dynamic macroeconomic models with intertemporally optimising agents. Within the framework of growth theory, dynamic models in continuous and discrete time…

The course provides an advanced, organised, and comprehensive discussion of theoretical and empirical research in public economics. It focuses on the relationship between the government and the market and arguments for and against…

A pass on the course is compulsory if the student is to obtain a master’s degree in Physical Geography. The course is carried out as an independent project. In the project the student should display an ability to apply and compile…

The aim of this course is to provide students with the theoretical understanding of how a geographic database is built-up and how it can be used. You will study key concepts for handling geographic databases with special focus on spatial…

The course contains a number of different basic components of spatial analysis, both in terms of theoretical background and analytical methods. Some of the concepts and techniques covered in the course are point pattern analysis,…

The aim of this course is to give the underlying mathematical and computer science theory required in GIS. This knowledge is necessary to evaluate the results in an analysis and to carry out more advanced analyses where the tools not are…

The aim of this course is to study the use of GIS in a client-server environment, where communication takes place through the Internet. Part of the course deals with computer screen cartography. The lectures deal with the most important…

The degree project requires a literature review and special studies. In addition, it includes a number of compulsory elements, in the form of lessons and seminars, which deal with, among other things, scientific writing in English and…

The course treats: Object-oriented programming style for scientific computing. SciPy/NumPy data structures. Examples of complex numerical algorithms from different fields within numerical analysis. Coupling to numerical libraries in C…

Simulation techniques is a field which merges experience in modelling with knowledge in Scientific Computing and programming skills. The course gives students in a late stage of their university studies the possibility to work, in small…

The course is preparatory for a master's thesis in numerical analysis. The overarching goal of the course is that students acquire in-depth knowledge in a specialised area of numerical analysis and are introduced to current research in the…

The course covers: Models of computational fluid dynamics Hyperbolic conservation laws and their basic properties (weak solutions, weak entropy solutions, shocks) Discontinuous Galerkin discretizations Simulations of gas dynamics…

The course treats: Methods for time integration: Euler’s method, the trapezoidal rule. Multistep methods: Adams' methods, backward differentiation formulae. Explicit and implicit Runge-Kutta methods. Error analysis, stability and…

The course gives an introduction to error estimates, convergence and stability, as well as existence and regularity of solutions to elliptic differential equations (PDEs). This is followed by an introduction to DUNE-FEM which discusses how…

The course provides students with a general overview of the development of Greek from Antiquity to the present, focusing on the period from the late Byzantine to the modern era with regard to changes in sound system, grammar and syntax…

This course is an introduction to the rapidly growing field of Corpus Linguistics and its application in Modern Greek studies. Corpus Linguistics (CL) is a method to retrieve data to study natural occurring language in different contexts…

The ability to argue well is one of the core competencies expected of citizens, politicians, companies, and students. The purpose of this course is to discuss and provide a vocabulary and instruments for the analysis, evaluation, and…

The course introduces different theories of translation, from classical contributions to modern theories that build on semiotics, the general science of meaning. Central questions dealt with include the nature of the act of translation,…

The fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning Feed-forward neural networks, convolutional neural networks, and the recurrent connections to a feed-forward neural network …

In this course you will learn modern statistical computing as viewed in data science through implementations in popular computing platforms such as R and Python. It covers the following topics: The R and Python environment: R packages…

The course provides an introduction to statistical analysis of text. You will study both methods based on classic statistical approaches (including Bayesian models) and modern approaches such as deep learning (recurrent neural networks)…

Machine learning refers to statistical model predictions that that improve through experience; as new data arrive, the model learns and adapts. For instance, the price that the supermarket can charge for advertisements depends critically…

This course covers advanced machine learning methods that are relevant for applications in business and economics, and is intended as a continuation of STAN51 Machine Learning from a Regression Perspective. Some of the topics covered…