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[ 973IDTT19 ] Subject Introduction to Digital Transformation and Technologies
Versionsauswahl
Workload Mode of examination Education level Study areas Responsible person Coordinating university
6 ECTS Course examination M1 - Master's programme 1. year Business Administration Stefan Koch Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Management 2023W
Objectives 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 recognize 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 optimization model and assess the result computed by the model. They will be able to design a simulation for a given scenario and analyze 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]
Subordinated subjects, modules and lectures