Trust in Digital Services

Teaching

Below you will find a current overview of the courses offered at the Trust in Digital Services department.

Teaching

The courses at the Department of Trust in Digital Services are primarily aimed at students of Industrial Engineering and Management, Business Informatics, Industrial Economics and Sustainable Management (NaMa).

IDTitleTypeCredit pointsTerm
70343Social and Economic Network AnalysisVL + UE6 ECTSeach semester
70348Data Science ToolboxVL + UE6 ECTSeach semester
70423Digital Service EngineeringVL + UE6 ECTSeach semester starting in summer 2022
Course types (according to §35 AllgStuPO): Lecture (VL), Tutorial (UE), Integrated classroom teaching (IV), Seminar (SE), Colloquium (CO), Practical training (PR), Projekt (PJ), and E-learning offerings.

Please refer to the course catalog for the current dates. We recommend attending the first date, as all organizational matters will be presented there, including course enrollment.

Data Science Toolbox

Course Overview

Course typeVL + UE
Credit points6 ECTS
TermEach semester
Workload4 SWS + exam preparation
LanguageGerman/English
Exam typeWritten exam (90 minutes, graded)
Degree programsInformation Systems Management (B.Sc./M.Sc.)
 Industrial Engineering and Management (B.Sc./M.Sc.)
 Business Mathematik (B.Sc./M.Sc.)
Kick-off19.04.2022
TimeTuesdays, 4.00-6.00 PM (c.t.) + Wednesdays, 12.00-2.00 PM (c.t.)
RoomH 0110
1st exam25.07.2022 (H 0105)
2nd exam11.10.2022 (MA 001)
Abkürzungen: Semesterwochenstunden (SWS), Vorlesung (VL), Übung (UE)

Course Description

Our world and in particular professional life are increasingly governed by data. Due to steadily amount, complexity, and importance of data, properly dealing with data has emerged as one, if not the most important competency today – basically regardless of business domain. This course will cover a “tool box” of methods for dealing with data and information, following the information life cycle. This includes approaches to collect data (e.g., by surveys, experiments, web crawling techniques), structuring and pre-processing (e.g., filtering, clustering), data visualization (e.g., static, online, networks), as well as analytical methods (network analysis). Moreover, the course covers fundamental statistical questions and applies the learned content directly within tools such as Java and R. The covered content is complemented and practically recapitulated by means of case studies and data-based examples. Moreover, the course is accompanied by guest lectures from practice. As a result, the course’s participants will learn to independently design and implement data-based projects.

The course’s objective is to convey a basic understanding for data-based projects and research objectives as well as practical skills to deal with data. This will include, among other aspects, the following topics: Survey and Experiment Design, Execution, and Evaluation • Web Crawling • Data Visualization • Filtering and Clustering • Data Cleaning and Pre-processing • (Social) Network Analysis • Machine Learning 101 • Linear Regression • Research Ethics.

Data Camp Classroom

Students who take this course can get free access to classroom content on Data Camp, a platform that offers coding classes online. Please contact us for more information.

Digital Service Engineering

Course Description

In this practice module, theoretical knowledge about digital business models and interactive data exploration acquired in other modules of the subject area is applied in practice. The module is dedicated to the prototype-ready development and design of digital services based on scientific methods and findings. The course can be conducted in cooperation with external mentors. Graduates of this module will demonstrate competencies in the following areas:

  • Data analysis and visual processing
  • Interactive data exploration
  • Analysis, development and optimization of user experience (User Experience [UX] Design)
  • Design of digital user interfaces and interaction processes (User Interface [UI] Design)
  • Pricing strategies

Furthermore, students who have completed the course are qualified to work on development tasks in teams, to document their approach and to present the results in a professional manner. They are able to independently design their own digital service concepts and realize functional website or platform prototypes

Examination Mode

The portfolio examination consists of the following study-related examination elements:

  • Functional prototype (web-based)*
  • Oral presentation
  • Written documentation

The above examination elements can be completed in both German and/or English.

*It must be possible for the supervisors to interactively operate the developed online platform without major disruptions.

Social and Economic Network Analysis

Course Overview

Course typeVL + UE
Credit points6 ECTS
TermEach semester
Work load4 SWS + exam preparation
LanguageGerman/English
Exam typeWritten exam (90 minutes, graded)
Degree programsInformation Systems Management (B.Sc./M.Sc.)
 Industrial Engineering and Management (B.Sc./M.Sc.)
 Business Mathematics (B.Sc./M.Sc.), or similar
Kick-off19.04.2022
TimeTuesdays + Thursdays, 2.00-4.00 PM (c.t.)
OrtH 1028
1st exam02.08.2022 (MA 001)
2nd exam11.10.2022 (MA 001)

Course description

Digital platforms are becoming increasingly important. Two-sided markets complement and extend traditional mode of consumption in many domains already today. Examples include short-term accommodation sharing, crowd work, delivery services, resale- and auction platforms, as well as ride sharing markets. Importantly, the platform principle bears several particularities which will be examined in this course. Central to the design and operation of digital platforms and associated business models is the existence of network effects, different user types und motives, and the paramount importance of trust and – based on this – the role of reputation systems and management. Case studies and guest lectures by partners both from industry and academia will complement the course.

The course’s objective is to convey a basic understanding of the paradigms and intricacies of digital platforms and platform business models. The course will, among other content, cover the following subjects: Sharing Economy and Crowd-based Capitalism • User Motives and Types • Economics of Multi-sided Markets • User Representation on Digital Platforms • Pricing Strategies • Trust and Reputation Systems.