DE

Modul

Data Science: Intelligent, Adaptive, and Learning Information Services [M-WIWI-105661]

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

Responsible

Organisation

  • KIT-Fakultät für Wirtschaftswissenschaften

Part of

Bricks

Identifier Name LP
T-WIWI-111219 Artificial Intelligence in Service Systems - Applications in Computer Vision 4.5
T-WIWI-102762 Business Dynamics 4.5
T-WIWI-102848 Personalization and Services 4.5
T-WIWI-102847 Recommender Systems 4.5
T-WIWI-111267 Intelligent Agent Architectures 4.5
T-WIWI-109921 Advanced Machine Learning 4.5
T-WIWI-110915 Intelligent Agents and Decision Theory 4.5

Competence Certificate

The assessment is carried out as partial exams (according to Section 4(2), 1 or 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. The assessment procedures are described for each course of the module seperately.

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

  • models, analyzes and optimizes the structure and dynamics of complex economic changes.
  • designs and develops intelligent, adaptive or learning agents as essential elements of information services.
  • knows the essential learning methods for this and can apply them (also on modern architectures) in a targeted manner.
  • develops and implements personalized services, especially in the area of recommender systems.
  • develops solutions in teams.

Prerequisites

None

Content

The Intelligent Architectures course addresses how to design modern agent-based systems. The focus here is on software architecture and design patterns relevant to learning systems. In addition, important machine learning methods that complete the intelligent system are discussed. Examples of systems presented include key-map architectures and genetic methods.
The impact of management decisions in complex systems is considered in Business Dynamics. Understanding, modeling, and simulating complex systems enables analysis, purposeful design, and optimization of markets, business processes, regulations, and entire enterprises.
Special problems of intelligent systems are covered in Personalization and Services and Recommendersystems. The content includes approaches and methods to design user-oriented services. The measurement and monitoring of service systems is discussed, the design of personalized offers is discussed and the generation of recommendations based on collected data from products and customers is shown. The importance of user modeling and recognition is addressed, as well as data security and privacy.

Recommendation

None

Workload

The total workload for this module is approximately 270 hours. For further information see German version.