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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. Hybrid Intelligence

Hybrid Intelligence (Master)

AIC-HYIN-M (AIC-HYNTELLI-M, only in SoSe 2024)
Lecture and excercise: 6 ECTS / 180 h / 4SWS

Supervisor: Prof. Dr. Milad Mirbabaie 

Language: English
Time: Tue, 8-12 o'clock Room: GU13/02.05

Contents: This module deepens the theoretical, conceptual and practical foundations of hybrid intelligence. Students acquire comprehensive knowledge about the integration of artificial intelligence and human intelligence in hybrid systems. The aim of Hybrid Intelligence is to combine the strengths of humans and machines by bringing together human capabilities such as creativity, emotional intelligence and contextual understanding with the computational capabilities of AI, such as data analysis and pattern recognition. The focus of this module is on theoretical concepts, methodological approaches and practical applications of Hybrid Intelligence.

Learning objectives/skills: The aim of the module is to provide students with in-depth knowledge and skills in the field of Hybrid Intelligence. After completing the module, students should be able to comprehensively understand relevant literature in relation to the interaction between humans and machines in order to be able to analyze and critically evaluate the concept of Hybrid Intelligence.

Structure:

The workload for this module is roughly broken down as follows:

  • Participation in the input sessions on the basics of Hybrid Intelligence
  • Self-study and preparation of paper presentations in individual or group work
  • Completion of in-depth assignments in individual or group work
  • Preparation of a term paper

Exam: term paper and presentation

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

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