Modul
Data Science: Intelligent, Adaptive, and Learning Information Services [M-WIWI-105661]
Credits
9Recurrence
Jedes SemesterDuration
1 SemesterLanguage
GermanLevel
4Version
2Responsible
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.