Entdecken Sie die spannenden Lehrveranstaltungen des Lehrstuhls von Prof. Detlef Schoder! Unser Angebot umfasst Vorlesungen und Seminare für die Studiengänge B.Sc. Wirtschaftsinformatik und M.Sc. Information Systems. Bei Fragen zu den einzelnen Veranstaltungen wenden Sie sich bitte direkt an den Lehrstuhl.

Für detaillierte Informationen zu den einzelnen Veranstaltungen und zur Organisation Ihres Studienverlaufs, schauen Sie bitte in die entsprechenden Modulhandbücher. 

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• Wirtschaftsinformatik als Wissenschaft
• Strategische Rolle von Informationssystemen
• Inner‐ und zwischenbetriebliche Geschäftsprozessintegration
• Electronic Commerce und Electronic Business
• Computer Supported Collaborative Work
• IT‐Sicherheit
• Ethische, soziale und politische Aspekte
• Informationsgüter
• Business Process Reengineering
• Internet der Dinge

• Begriffe, Schutzziele, Bedrohungsklassen
• Historische Fallbeispiele und daraus folgende Schlüsse für zukünftige Situationen
• Vorstellung konkreter Angriffstechniken und Bedrohungen
• Design sicherer Systeme (Berücksichtigung im Entwicklungsprozess, Frameworks, ISO/IEC 27001, Risikoanalyse
• Anerkannte Rahmenwerke (BSI Grundschutz, ISO 27001, Business Continuity Management, ...)
• Sicherheitsmodelle
• Grundlagen kryptographischer Verfahren
• Authentifikationsverfahren und Identitätsmanagement
• Mobile Security
• Incident Response und IT-Forensik
• Rechtliche Rahmenbedingungen

• Projektplanung im Kontext wissenschaftlicher Arbeiten
• Struktur und Argumentation in wissenschaftlichen Arbeiten: Problemstellung, Zielsetzung, Begriffssystem, Gliederung
• Umgang mit wissenschaftlicher Literatur: Literaturrecherche, Literaturverwaltung, Literaturauswertung, Referenzierung und Zitation in wissenschaftlichen Arbeiten
• Wissenschaftliches Schreiben • Formale Vorgaben
• Verfassen, präsentieren und verteidigen einer eigenen wissenschaftlichen Arbeit

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

• Conceptual basics of relevant technologies (including sensors, RFID, telecommunication)

• 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 of adding value

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

This seminar takes place in cooperation with MIT, University of Cologne and University of Bamberg and shows how to measure happiness and creativity through 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 take on sub-projects of current research projects of the chair. The course enables participants to write and publish and academic IS paper. 

Exemplary topics: 

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

• Assess recent developments in AI, in particular the role of Artificial Neural Networks (Neural Networks, NNs)
• Learn and deploy prominent computer vision models (Convolutional Neural Networks, CNNs)
• Learn and deploy most recent language models and transformer approaches to “compute text” (Natural Language Processing, NLP)
• Learn about the challenges semi-structured and unstructured data poses for analysis
• Think of (new) applications in the field of Information Management based on the processing of unstructured and semi-structured data
• Get sensitive towards managerial implications of the advancements in AI for Information Management
• How to create AI-driven innovations (product, 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 capability
• What does the intensified application of AI mean for the future of work and separation of work between humans and machines
• Learn about “Responsible AI” and seize the challenges of an „eXplainable AI (XAI)“
• Understand the fundamental problem of bias (in data, in models, in algorithms) and ethical challenges. Also get equipped with concepts and methods to alleviate problems of unfair profiling and incompliant use of data.
• Discuss the current state of AI regulation

• The Digital Transformation phenomenon: What do we understand by “Digital Transformation”?
• Key Business Trends: Which trends affect value creation? Which trends a digital leader has to look out for?
• Digital Leadership: What are the most important topics for a digital leader?
• Business Patterns: What is a business model and how to describe it?
• Managing External Resources: Why we need to extent traditional information management towards IM 2.0. What are strategic implications of public social media for companies?
• Everything-as-a-Service: From products to services / the economics of cloud computing /servitization / sharing economy
• Platforms: What are platform-type business models and how are they different?
• What are managerial decisions regarding platform businesses?
• Competing on Analytics: How can companies gain competitive advantage through better decision making?
• Blockchain and Crypto: What is it? How to transform centralized organizations; DeFi, DAO, Smart Contracts, Use Cases Bitcoin and Etherium

This course delves into 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.