The Description of the module you find at the Module Handbooks:

Module Handbook Business Analytics

Module Handbook Artificial Intelligence and Machine Learning for Connected Systems

 

Topics:

• Introduction
• Concept description and definitions
• Data preparation
• Discovering, ingesting, and exploring data
• Transforming data into analytics-ready data
• Association rules
• Clustering
• Classification
• Data mining
• Model assessment and validation

Complementary content:

• Network analysis
• Process Mining: Event Logs, Process Discovery, Conformance Checking, Logbased Verification (Toolset: ProM, Disco and Celonis)
• DataWarehousing: ETL Process, DataWarehouse Components & Architecture, Multi-dimensional data model, ROLAPS
  
   

The course aims to present data mining and knowledge discovery concepts, methods and techniques.

 

The study program combines self-study and group work in a flexible online learning environment. Students have access to video lectures, a detailed and user-friendly script tailored for working professionals, as well as interactive quizzes and exercises. Regular tutorial sessions and online office hours with mentors support the learning process, while discussion forums facilitate exchange among students. For more detailed information, please refer to the module handbook.

Algorithmics, data structures, statistics
 

Regular participation in online seminars will help you solving exercises, which have to be loaded up to the learning management system after request of the mentor. Passing the exercises successfully is recommended for participation in the final examination at Ulm University.
 

After finishing your exame successfully you will get a certificate and a supplement, which will list the contents of the module and the competencies you have acquired. In the supplement the responsible person for the module confirms you the equivalent of 6 credit points (ECTS).
 

Study fees and participation fees