Vorlesungsverzeichnis Master Wirtschaftsinformatik

Advanced ISD project is a course wherein students must put their pre-acquired knowledge (in the Information Systems Development and Web-based Information Systems) into practice. After providing a brief introduction on some web frameworks and on API, students are meant to work in groups to develop a Web-based Information System.

Students will explore how to establish effective governance frameworks that enable businesses to leverage AI while managing risks. The curriculum also delves into strategic planning for generative AI, illustrating its potential to revolutionize business models and enhance operational efficiency. Additionally, students will learn about trans-forming companies towards AI companies, including changing organizational culture to thrive in the AI era. Key points are:

• Data and AI governance: Frameworks for businesses for seizing opportunities while mitigating risks
• Data and AI strategy with focus on Generative AI
• AI Transformation: Leading a company into the AI area
• Ethical considerations in AI

BPM and Organisational Practice explores Business Process Management (BPM) through an organisational-studies lens, so it is a BPM elective. Emphasizing the duality of stability and change in organisational work, the course covers the factors, mechanisms, and interventions that affect how processes behave over time. The course covers six primary topics:

• Organisation theory
• Process- and practice-based research
• Organisational routines
• Intra-organisational dynamics and endogenous change
• Organisational learning, unlearning, and forgetting
• The role of agency and intention in the execution of organisational work

Data and Application Security provides an introduction to cyber security and covers topics related to information and communication security. This is one of the core subject areas of the degree programme, and the course provides a foundation for choosing further electives in the area of cybersecurity. The course covers the following topics:

• Security goals and design principles
• Economic aspects of security and risk analysis
• Basics of cryptography
• Authentication and access control
• Key instruments of network security
• Key instruments of web security
• Software security, vulnerabilities, and attacks
• Email and mobile device security

Data Science and Artificial Intelligence covers statistical and exploratory techniques that are used to make sense of the vast and complex data sets that have emerged in business. Data Science and Artificial Intelligence is one of the core topics of the degree programme, so the course also provides a basis on which students can choose their electives. Students learn to detect patterns in large data sets in quantitative and qualitative formats to translate them into actionable insights. The course covers five primary topics, but also touches upon other topics such as contemporary ethical concerns. It is complemented by Hands-on labs with Python.

• Data visualisation and exploration
•Supervised learning techniques for regression and classification
• Un- and self-supervised learning techniques
• Deep learning fundamentals
• Generative artificial intelligence including large language models

Deep Learning and Advanced AI Techniques cover the basics of deep learning and advanced AI techniques and recent technological trends. It also includes a few aspects of generative AI. The course covers:

• Fundamentals of artificial intelligence
• Reinforcement learning – Learning to play games and beyond
• Fundamentals of deep learning, network design, and training
• Transfer learning and pre-trained models
• Data augmentation and synthesis
• Core ideas of: Graph Neural Networks, Autoencoders, Generative adversarial networks (GANs), recurrent neural networks, convolutional neural networks, diffusion models
• Explainability and interpretability in AI
• Case studies and applications in various industries and for various tasks
• Recent trends and future directions in AI and deep learning

The digitization of society and business is transforming the way we consume, work, interact and create, leading to a new era centered on the digital user and their evolving needs. This shift presents both opportunities and challenges for companies, forcing them to adapt their business models and strategies.
Building on the fundamentals of Digital Innovation, this lecture will explore the integration of digital technologies, par-ticularly within established companies, and how organizations can develop digital transformation strategies that foster innovation, optimize operations, and drive cultural change. The course is structured around three core themes:

• Digital Transformation of Value-Based Offerings: Examining how firms can utilize digital tools and technologies to create and enhance value propositions.
• Optimization of Existing Business Processes: Analyzing ways in which digital technologies can help streamline operations and improve efficiency.
• Driving Cultural Change in Organizations: Investigating the organizational dynamics and leadership strategies essential for fostering a digital culture.

Through real-world case studies, students will engage with practical examples of successful digital transformation ef-forts, focusing on incumbent firms. By the end of the course, students will have a comprehensive understanding of how digital technologies can drive sustainable change and competitive advantage.

The Educational Journey covers lectures at a foreign university, company visits, and leisure activities. Course topics change from semester to semester.

• Planning security: Even if the study trip cannot take place, there is the possibility that you can acquire the 3 ECTS through an alternative examination performance

Emerging IT Topics addresses recent technological trends and developments in research and business, so its content can be adapted quickly to the job market’s emerging needs. Accordingly, the course content changes from
semester to semester.

Extracurriculare Activities comprise of various activities that are not linked to the Curriculum of the MSc in Information Systems, which are optional and further support the studying of the Master programme.

Information Systems Modelling focuses on systems analysis and design. In particular, the course covers methods of and approaches to modelling information systems in organisations. The course covers five primary topics:

• Introduction to object-oriented systems
• Project planning and initiation
• Requirements analysis (i.e. requirements gathering and structuring)
• Information systems modelling (i.e. UML modelling languages)
• Information systems documentation

In the Innovation Lab seminar, students work in small groups to solve practical IT problems in cooperation with multiple regional companies. Representatives of these companies regularly provide students with feedback at the university and take part in networking events. The seminar thus also supports dialogue between regional industry and the university, helping students to interact with world-renowned companies right from the start of their studies. Students learn to work independently, to work in a team, to take responsibility, and to present project results effectively. In addition to creative thinking, the use of skills related to problem-solving, organizing and planning, communication, and project management is encouraged. Course topics change from semester to semester.

In their Master’s Thesis, students use scientific methods and work in accordance with standards of scientific writing. The master's thesis is typically related to one of the four subject areas that constitute the core of the curriculum (i.e., Business Process Management, Data and Application Security, Data Science, and Digital Innovation).

In the Research Seminar course, students learn to apply in practice what they learned in the Research Methods course. The seminar covers issues related to identifying and formulating research questions, choosing a suitable research design to use in answering these questions, evaluating the feasibility of a planned research study, and writing research proposals. Together with faculty, students develop research proposals (so-called “exposés”) for their master’s theses

Security Management covers technical and organisational methods for the definition and implementation of security policies. The course covers five primary topics:

• People, processes, and strategic planning
• Risk management
• Regulatory compliance, aw, and ethics
• Security analysis, safeguards, and frameworks
• Maturity and performance measurement