Kompetenzbereiche: Wissen und Verstehen; Einsatz, Anwendung und Erzeugung von Wissen; Kommunikation und Kooperation; Wissenschaftliches Selbstverständnis/Professionalität.

Students can specifically (in terms of content)...
- explain the concept of machine learning (ML) and classify it in the context of artificial intelligence (AI),
- name, differentiate, describe and explain the concepts, methods and models of supervised and unsupervised learning,
- understand the mathematical and statistical foundations as well as in-depth methods and models of machine learning,
- name and explain basic and advanced methods of data analysis and data pre-processing, in particular procurement, transformation, cleansing, partitioning, scaling, visualization and static description,
- describe the complete process of carrying out an ML project from the analysis and pre-processing of data to the application of methods and development of models through to the post-processing of data (e.g. model-based forecasting).
Students have/are generally able to...
- significantly deepened and expanded their knowledge,
- define and interpret the special features and limitations of the methods and models,
- develop, on the basis of existing knowledge, both research- and application-oriented
develop and apply independent generalized and specialized ideas on the methods and models in a research and application-oriented manner,
- weigh up the correctness of their extended and, if necessary, independently modified knowledge, taking into account scientific-disciplinary (e.g. mathematics and statistics) and methodological considerations, and solve scientific and practical problems on this basis.

Students can specifically (in terms of content) ...
- identify and assess the application potential of AI or ML in different and possibly unknown application contexts,
- solve specific problems largely independently using Python.

Students can generally ...
- integrate new information into the existing knowledge network and/or further process and develop existing knowledge and thus acquire new knowledge independently,
- apply their knowledge, understanding and problem-solving skills in new, unfamiliar and unpredictable situations that are related to their field of study in a broader or multidisciplinary context by integrating existing and new knowledge in complex contexts,
- deal with a high degree of complexity and intricacy with regard to scientific and practical tasks,
- making scientifically sound decisions,
- designing research questions from a purely scientific point of view, selecting well-founded research methods and interpreting research results critically.

Students can generally ...
- engage in discussions with representatives of different academic and non-academic fields of activity as well as on alternative, theoretically justifiable solutions to problems,
- integrate participants into tasks in a goal-oriented manner, taking into account the respective group situation,
- recognize potential for conflict in cooperation with others and reflect on this against the background of cross-situational conditions,
- ensure the implementation of solution processes appropriate to the situation through constructive, conceptual action

Students can generally ...
- develop a professional self-image that is oriented towards goals and standards of professional action both in academia and in professional fields outside academia.
- justify their own professional actions with theoretical and methodological knowledge and reflect on alternative approaches.
- judge their own abilities, make autonomous use of relevant freedom of organization and decision-making and develop these further under guidance.
- recognize situation-appropriate and cross-situational framework conditions for professional action and reflect on decisions in an ethical and responsible manner.
- critically reflect on their professional actions in relation to social expectations and consequences and further develop their professional actions.