Students are enabled to creatively work on complex quantitative tasks from the fields of business or technology, in particular using suitable software applications with the methods of applied mathematics. This includes the competence to transfer a concrete problem into an abstract model and then to analyse and solve it using computer-aided methods.

For this purpose, the degree course imparts a broad and integrated knowledge including the scientific foundations and practical application of applied mathematics, as well as a critical understanding of the most important theories and methods of applied mathematics and mathematical modelling. In addition to a sound mathematical specialist knowledge and the ability to implement mathematical methods on the computer, students will acquire extensive competences in analysing, structuring, modelling and formalising application problems and thus universally applicable problem-solving skills. Overall, they will thus possess knowledge and experience that enable them to independently develop the methods they have learned scientifically. They will be able to define, reflect and evaluate goals for their learning and work processes and thus design these processes independently and sustainably.

The students will try out these competences in the specialisations in Business Mathematics and Technomathematics and will be able to select basic relevant subject knowledge at the interfaces to the business and technical disciplines for this purpose. In this way, they will be able to incorporate scientific and technical progress in an application-oriented manner when solving their professional tasks and to react creatively to changing requirements of the professional world.

The students will acquire the competence to work in interdisciplinary expert teams, to guide the professional development of others and to deal with problems in a team with foresight. They will be able to argue the solutions they have determined both to mathematical experts and to experts in the respective application disciplines and develop them further in interdisciplinary teams.

• Mathematical conceptualisations and proofs

The students will acquire basic competences in the field of mathematical proof and axiomatic mathematical concept formation. They will get to know the technical terms of analysis and linear algebra and will be able to comprehend proofs in these subject areas and formulate them themselves in simple cases, stringently using the mathematical notations. The basic competences acquired in the courses on analysis and linear algebra will enable the students to comprehend the axiomatic structure in the further course of studies, also in the subjects of applied mathematics. They will be able to understand mathematically abstractly formulated statements and proofs about the properties and behaviour of procedures and methods of applied mathematics.

• Algorithms and schematic calculations

Students will learn a wide range of algorithms and computational methods for solving problems from the subject areas of applied mathematics. They will acquire the skill to perform these computational procedures with the help of suitable software applications and will be able to interpret the output of these programs using their theoretical mathematical knowledge of these procedures. The experience gained in this way will enable the students to independently familiarise themselves with procedures and software systems that are new to them and to gain the necessary application security through appropriate literature studies and application experiments.

• Mathematical modelling skills

The students will gain experience in how problems from business and technology can be translated into mathematical problems and then solved with the help of suitable mathematical calculation methods. In addition to extensive knowledge in a variety of examples, the students will know the essential steps of the abstract modelling process. Overall, they will thus be enabled to select suitable models and to critically analyse the respective results against the background of the simplifying assumptions usually made in the process.