DE

Modul

Informatics & Machine Learning [M-WIWI-105880]

Credits
9
Recurrence
Jedes Semester
Duration
2 Semester
Language
German/English
Level
4
Version
1

Responsible

Organisation

  • KIT-Fakultät für Wirtschaftswissenschaften

Part of

Bricks

Identifier Name LP
T-WIWI-102666 Knowledge Discovery 4.5
T-WIWI-109799 Process Mining 4.5
T-WIWI-106423 Information Service Engineering 4.5
T-WIWI-110848 Semantic Web Technologies 4.5
T-WIWI-106341 Machine Learning 2 – Advanced Methods 4.5
T-WIWI-106340 Machine Learning 1 - Basic Methods 4.5
T-WIWI-102661 Database Systems and XML 4.5

Competence Certificate

The assessment is carried out as partial exams (according to Section 4(2) of the examination regulation) of the single courses of this module, whose sum of credits must meet the minimum requirement of credits of this module. For passing the module exam in every singled partial exam the respective minimum requirements has to be achieved.

The examinations are offered every semester. Re-examinations are offered at every ordinary examination date. The assessment procedures are described for each course of the module separately.

When every singled examination is passed, the overall grade of the module is the average of the grades for each course weighted by the credits and truncated after the first decimal.

Competence Goal

The student

  • has the ability to master methods and tools in a complex discipline and to demonstrate innovativeness regarding the methods used,
  • knows the principles and methods in the context of their application in practice,
  • is able to grasp and apply the rapid developments in the field of Informatics, which are encountered in work life, quickly and correctly, based on a fundamental understanding of the concepts and methods of Informatics,
  • is capable of finding and defending arguments for solving problems.

Content

The thematic focus will be based on the choice of courses in the areas of Applied Technical Cognitive Systems, Business Information Systems, Information Service Engineering or Web Science. 

Workload

The total workload for this module is approximately 270 hours. The total number of hours per course is calculated from the time required to attend the lectures and exercises, as well as the examination times and the time required for an average student to achieve the learning objectives of the module.