KI und Data Science in der Anwendung

Intended Audience:

Master Wirtschaftsinformatik

Master International Economics

Master Development Economics

Master Management

Master Finanzen, Rechnungswesen und Steuern

Master Angewandte Statistik

Master Wirtschaftspädagogik

Master History of Global Markets


Open for PhD Students


Language:

German



Cycle:

Every SummerTerm



Requirements:

None



UniVZ:

800240



Workload:

Blocked Seminar, Final Presentation

Summer Term 2026

Please check this website regularly for updates.

Seminar

• 
  
  01.03.2026
  8:00
  
  
  Start of Registration
  
  
              Stud.IP
  
  


• 
  
  20.04.2026
  09:00 - 17:00
  
  
  Block 1
  
  
              MZG 8.136
  
  


• 
  
  09.07.2026
  09:00 - 17:00
  
  
  Block 2
  
  
              MZG 8.163
  
  


• 
  
  10.07.2026
  09:00 - 17:00
  
  
  Block 3
  
  
              MZG 8.136
  
  

read more

Students must register for the exam via FlexNow





Examination:

Final Presentation

6 ECTS




Course Content

Data is the central basis for business decisions, the quality of which increasingly
depends on making existing data usable. The course addresses goals, challenges, and general conditions.
A central element of this course is the application of selected methods and tools to specific use cases and a presentation of the findings.


This course covers the following topics, among others:

• Data-based business decisions: approaches & objectives, framework conditions & challenges


• Methods for data analysis: machine learning, deep learning, AI, etc.


• Tools for data analysis


• Presentation and discussion of specific practical use cases

Learning Objectives:

By the end of this seminar, students will

• gain a fundamental understanding of the benefits and use of data in business
  decisions,


• learn about key aspects and challenges in data processing based on selected use
  cases,


• get an overview of how relevant software tools work and how to use them,


• develop an understanding of the possibilities and limitations of analytical and AI based
  methods in the real world applications.

Important info!

The number of participants is limited to 20.