LFU:online

Prerequisites for registration: none

Learning Outcome: Students of this module have acquired the ability to use selected mathematical software and to implement simple mathematic algorithms into selected software language. They have learned how to transfer criteria into mathematical content and formal design in a text. Furthermore, they know the occupational profile of mathematicians and have gained an overview of the topic of equality and gender as well as of their study programme.

Prerequisites for registration: none

Learning Outcome: Students of this module understand the content of the lectures and they can reproduce and apply it. They can produce similar content for themselves. With the help of software they can illustrate problems of Descriptive Geometry and also apply them appropriately. Moreover, they have acquired a basic understanding of the methods of Geometry.

Prerequisites for registration: none

Learning Outcome: Students who have completed that module have acquired a deepened knowledge of a branch of higher mathematics by autonomous studies. Moreover they are familiar with relevant mathematical literature and can judge its mathematical content. They are able to examine problems of higher mathematics in a creative and methodically correct manner and to present the result of those examinations in written form and orally as to be understood well by experts. The contents of the seminars are oriented on current research topics.

Prerequisites for registration: none

Learning Outcome: Having successfully completed this module, students are able to actively participate in the discussion of the current state of knowledge in the area of the dissertation topic and can critically reflect on and discuss issues with experts of the chosen partial discipline. On this basis, they are able to make their own contributions to research.Likewise the students have interface knowledge at a high professional level which is needed for the implementation of the dissertation.

Prerequisites for registration: none

Learning Outcome: - The students know the most important application possibilities of scientific computing as well as its potential to provide interdisciplinary efficient answers to current questions in research, economy and society. They are aware of gender issues and gender relations in the natural and technical sciences. - Students understand aspects of conventional computer architecture particularly relevant to scientific computing, as well as useful techniques for software development and management, which also guide forms of collaborative work. They are able to implement simple numerical algorithms - basic components of more complex simulations - and to analyse their properties. - They can explain and apply the scientific principles and basic methods of mathematical modelling as a basis for simulation. They are able to analyse simple existing models, select and apply suitable ones from established procedures for their evaluation, and interpret the resulting data in a professional manner.

Prerequisites for registration: none

Learning Outcome: - Students will be familiar with representative examples of applications of scientific computing in various disciplines as well as the subject-specific software used to process them and will be able to discuss both from the perspectives of the various disciplines. - They have the competence - independently and with original ambition - to elicit meaningful models for selected problems from the practice of scientific computing, to construct suitable simulations and to implement, execute and evaluate them efficiently on suitably selected hardware, and to critically evaluate the results obtained. - They have the skills to visualise simulation data in a professional and descriptive manner and to manage it according to the rules of good scientific practice. They are able to communicate, explain, and discuss findings obtained from simulations, useful visualisations, and prerequisites and limitations of the statements made.

Prerequisites for registration: none

Learning Outcome: - The students know the most important application possibilities of scientific computing as well as its potential to provide interdisciplinary efficient answers to current questions in research, economy and society. They are aware of gender issues and gender relations in the natural and technical sciences. - Students understand aspects of conventional computer architecture particularly relevant to scientific computing, as well as useful techniques for software development and management, which also guide forms of collaborative work. They are able to implement simple numerical algorithms - basic components of more complex simulations - and to analyse their properties. - They can explain and apply the scientific principles and basic methods of mathematical modelling as a basis for simulation. They are able to analyse simple existing models, select and apply suitable ones from established procedures for their evaluation, and interpret the resulting data in a professional manner.

Prerequisites for registration: none

Learning Outcome: - Students will be familiar with representative examples of applications of scientific computing in various disciplines as well as the subject-specific software used to process them and will be able to discuss both from the perspectives of the various disciplines. - They have the competence - independently and with original ambition - to elicit meaningful models for selected problems from the practice of scientific computing, to construct suitable simulations and to implement, execute and evaluate them efficiently on suitably selected hardware, and to critically evaluate the results obtained. - They have the skills to visualise simulation data in a professional and descriptive manner and to manage it according to the rules of good scientific practice. They are able to communicate, explain, and discuss findings obtained from simulations, useful visualisations, and prerequisites and limitations of the statements made.