Discover the exciting courses offered by Prof. Detlef Schoder’s chair! We offer lectures and seminars for the B.Sc. Information Systems and M.Sc. Information Systems programs. If you have any questions about specific courses, please contact the team directly.

For detailed information on individual courses and on planning your academic path, please consult the corresponding module catalogues.

Please note that the module catalogues reflect the current and binding status. The information on this page may not be up to date.

• Business Informatics as a Field of Study
• The Strategic Role of Information Systems
• Intra- and Inter-organizational Business Process Integration
• Electronic Commerce and Electronic Business
• Computer-Supported Collaborative Work
• IT Security
• Ethical, Social, and Political Aspects
• Information Assets
• Business Process Reengineering
• Internet of Things

• Terms, Protection Objectives, Threat Classes
• Historical case studies and the resulting conclusions for future situations
• Presentation of specific attack techniques and threats
• Design of secure systems (integration into the development process, frameworks, ISO/IEC 27001, risk analysis
• Recognized frameworks (BSI Basic Protection, ISO 27001, Business Continuity Management, ...)
• Security models
• Fundamentals of cryptographic methods
• Authentication methods and identity management
• Mobile Security
• Incident Response and IT Forensics
• Legal Framework

• Project Planning in the Context of Academic Writing
• Structure and Argumentation in Academic Papers: Problem Statement, Objectives, Conceptual Framework, Outline
• Working with Academic Literature: Literature Search, Literature Management, Literature Analysis, Referencing, and Citation in Academic Papers
• Academic Writing • Formal Requirements
• Writing, Presenting, and Defending Your Own Academic Paper

• Current IT trends and the transformation of e-business into “ambient business” in the context of networked and computerized objects and environments (Internet of Things, smart environments)

• Conceptual foundations of relevant technologies (including sensors, RFID, and telecommunications)

• Design and applications of smart environments

• Design of intuitive human-computer interaction (HCI)

• Context awareness and context-based services

• Freely offering and sharing information as a way to add value

• Economic, social, and ethical effects of increasingly ubiquitous information technology

This seminar is held in collaboration with MIT, the University of Cologne, and the University of Bamberg, and demonstrates how to measure happiness and creativity by analyzing collective consciousness within organizations and on the Internet using social media analysis.

• Collaborative Innovation Networks (COINs)
• swarm creativity, and coolhunting/coolfarming
• Social network analysis
• Sentiment analysis
• Digital platforms for collaboration and creativity

Participants work on subprojects of the chair's current research projects. The course enables participants to write and publish an academic IS paper.

Examples of topics:

• Business Analytics
• Artificial Intelligence in Trading, Healthcare, and Logistics
• Openness
• Smart Harvesting
• AI-Generated Aesthetic Layout
• Generative AI

• Assess recent developments in AI, particularly the role of artificial neural networks (neural networks, NNs)
• Learn and deploy leading computer vision models (Convolutional Neural Networks, CNNs)
• Learn and deploy the latest language models and transformer approaches for “text processing” (Natural Language Processing, NLP)
• Learn about the challenges that semi-structured and unstructured data pose for analysis
• Identify (new) applications in the field of information management based on the processing of unstructured and semi-structured data
• Develop an awareness of the managerial implications of advancements in AI for information management
• How to create AI-driven innovations (products, processes, business models)
• Learn about the role of the data value chain and the transformative power of AI for data-driven businesses
• Understand how companies build AI capabilities
• What does the increased use of AI mean for the future of work and the division of labor between humans and machines
• Learn about “Responsible AI” and address the challenges of “Explainable AI (XAI)”
• Understand the fundamental problem of bias (in data, models, and algorithms) and the associated ethical challenges. Also, gain the concepts and methods needed to mitigate issues of unfair profiling and non-compliant data use.
• Discuss the current state of AI regulation

• The Digital Transformation Phenomenon: What Do We Mean by “Digital Transformation”?
• Key Business Trends: Which trends influence value creation? Which trends should a digital leader be aware of?
• Digital Leadership: What are the most important topics for a digital leader?
• Business Models: What is a business model, and how do we describe it?
• Managing External Resources: Why do we need to expand traditional information management toward IM 2.0? What are the strategic implications of public social media for companies?
• Everything-as-a-Service: From products to services / the economics of cloud computing / servitization / the sharing economy
• Platforms: What are platform-based business models, and how do they differ?
• What are the key managerial decisions regarding platform businesses?
• Competing on Analytics: How can companies gain a competitive advantage through better decision-making?
• Blockchain and Crypto: What are they? How to transform centralized organizations; DeFi, DAO, smart contracts, use cases for Bitcoin and Ethereum

This course explores the next frontier of artificial intelligence: autonomous AI agents. Moving beyond simple AI models that predict or classify, we will explore intelligent systems that can perceive their environment, reason, make decisions, and act to achieve complex goals. As AI continues to evolve from a tool for analysis into an active partner in digital processes, understanding AI agents is becoming critical for future business and IT leaders.

• Foundations and Evolution: From symbolic AI to LLM-driven architectures.
• Core Components of Modern Agents: Understanding perception, memory, planning, and action loops (e.g., ReAct).
• The Role of Large Language Models (LLMs): How LLMs serve as the core reasoning engine for agents.
• Agentic Design Patterns: Developing agents that can use tools, access APIs, and interact with external systems.
• Managerial Implications & Strategic Value: Identifying high-impact use cases, assessing ROI, and managing the integration of AI agents into business processes.
• Ethical and Governance Challenges: Discussing the risks and responsibilities of deploying autonomous systems in real-world scenarios.