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Information Systems and Applied Computer Sciences

Chair of Information Systems, esp. AI Engineering in Companies

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Information Systems
  6. Chair of Information Systems, esp. AI Engineering in Companies
  7. Teaching
  8. Master
  9. [Translate to English:] Digital Transformation and AI-based Systems

Practical Project: Digital Transformation and AI-based Systems

AIC-DITAIS-M
WI Project: 6ECTS / 180h / 4SWS

Module coordinator: Prof. Dr. Milad Mirbabaie

Language of instruction: English
Time: n.n.

Content: The course discusses the upcoming societal changes in relation to the use of artificial intelligence and assistive technologies. It deals with relevant topics and analyzes them on the basis of empirical and theoretical studies. The focus is on how society reacts to new technologies and weighs up their potential advantages and disadvantages. It highlights current scientific and socially significant issues and examines advances through a critical lens that utilizes both empirical and theoretical literature.

Learning objectives/skills: After completing the course, students will be able to classify the main areas of influence of digital change, particularly in relation to society. They not only understand the technological and conceptual foundations, but are also familiar with ethical considerations that are incorporated into the evaluation. They understand the interdisciplinary nature of research and practical application, particularly with regard to the changes in the social landscape brought about by digital technologies such as AI and assistance systems. Students are able to assess the overarching role of digital technologies in the social context. They are proficient in common methods and technologies and can apply them prototypically. They are able to interpret and critically evaluate empirical and theoretical literature.

Examination form: term paper and colloquium

Other information:
Frequency: winter semester
Minimum duration of the module: 1 semester

This is a course for Master students. No admission requirements. No special prior knowledge is necessary for this module.

If you are interested in this course, please register via FlexNow! If your enrollment was successful, you can attend. Please be sure to attend the first session of the semester. You will receive the enrollment information for the corresponding VC course at the kick-off session.

You can also find all information in UnivIS.