| Ziele |
(*)Learning outcomes:
On successful completion of this course, the students will be able to:
- LO1: Differentiate between digitization, digitalization and digital transformation and connect it with the information function in organizations. [Relevant Theory, Digital transformation, Business management qualifications, Interdisciplinary skills]
- LO2: Analyze and evaluate different tools and methods for a given challenge and apply the selected tool and method. [Relevant Theory, Digital transformation, Business management qualifications, Interdisciplinary skills, Research Skills and Methodological competencies, Social Skills, Interaction with companies, empirical/practical projects]
- LO3: Use modeling techniques (BPMN 2.0, UML or EPK) to work on complex and complicated digital transformation projects [Relevant Theory, Digital transformation, Business management qualifications, Interdisciplinary skills, Research Skills and Methodological competencies, Social Skills, Interaction with companies, empirical/practical projects]
- LO4: Distinguish good and bad practices used by descriptive analytics (bias, misleading, etc.) and apply knowledge in practical exercises. [Ethics, Responsibility and Sustainability (ERS), Analytical skills, Digital transformation]
- LO5: Choose right prediction models and design the model for chosen practical example. They will be able to recognise the ethics problems of machine learning. [Ethics, Responsibility and Sustainability (ERS), Analytical skills, Problem Solving and Reflections Skills, Research Skills and Methodological competencies]
- LO6: Acquire the tools necessary to formulate a problem as an optimisation model and assess the result computed by the model. They will be able to design a simulation for a given scenario and analyse the outcomes of the simulation. [Problem Solving and Reflections Skills, Analytical skills, Research Skills and Methodological competencies]
- LO7: Apply R and RStudio to solve problems arising in Descriptive, Predictive and Prescriptive analytics. [Digital skills, empirical/practical projects]
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