DE

Modul

Data Science: Advanced CRM [M-WIWI-101470]

Credits
9
Recurrence
Jedes Semester
Duration
1 Semester
Language
German
Level
4
Version
6

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-103549 Intelligent CRM Architectures 4.5
T-WIWI-105778 Service Analytics A 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

  • understand service competition as a sustainable competitive strategy and understand the effects of service competition on the design of markets, products, processes and services,
  • models, analyzes and optimizes the structure and dynamics of complex business applications,
  • develops and realizes personalized services, especially in the field of recommendation services,
  • analyzes social networks and knows their application field in CRM,
  • works in teams.

Prerequisites

None

Content

Building on the basics of CRM from the Bachelor's degree program, the module "Data Science: Advanced CRM" is focusing on the use of information technology and its related economic issues in the CRM environment.The course "Intelligent CRM Architectures" deals with the design of modern intelligent systems. The focus is on the software architecture and design patterns that are relevant to learning systems. It also covers important aspects of machine learning that complete the picture of an intelligent system. Examples of presented systems are "Taste Map"-architectures, "Counting Services", as well as architectures of "Business Games".The impact of management decisions in complex systems are considered in the course "Business dynamics". The understanding, modeling and simulation of complex systems allows the analysis, the goal-oriented design and the optimization of markets, business processes and regulations throughout the company.Specific problems of intelligent systems are covered in the courses "Personalization and Services", "Recommender Systems", "Service Analytics" and "Social Network Analysis in CRM". The content includes procedures and methods to create user-oriented services. The measurement and monitoring of service systems, the design of personalized offers, and the generation of recommendations based on the collected data of products and customers are discussed. The importance of user modeling and -recognition, data security and privacy are adressed as well.

Recommendation

None

Workload

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