Current Semester (WiSe)

Contents: Understanding, applying, and critically reflecting on AI. Technical foundations, practical use, and the ethical, legal, and organizational impacts of AI.

Learning and qualification objectives: Students learn to understand generative AI and LLMs, use them purposefully, and critically assess their opportunities, risks, and impact on organizations.

Examination format: Written examination (100%) during the examination period

Further information

Course Content: Fundamentals of modern web development, including the architecture of web applications, client–server communication, and the HTTP protocol; Python as a server-side programming language; JavaScript for client-side programming, DOM manipulation, and asynchronous communication; use of a web framework for database-driven web applications; data modeling and database integration; responsive web design with HTML5 and CSS3; development of a complete web application.

Learning Objectives and Competencies: Upon successful completion of the course, students will be able to understand and explain the architecture of web applications; apply Python and JavaScript purposefully in web development; develop structured, database-driven web applications using a web framework; integrate frontend and backend technologies; design data models and implement database connections; create user-friendly web interfaces; use version control systems for collaborative development; and independently plan, implement, and present web projects.

Assessment: Individual completion of practical exercises (approx. 30%) and the development and presentation of a web development project in groups (approx. 70%). Each component must be passed independently. The exact weighting will be announced at the beginning of the module.

Further information

Contents: Students are assigned practice-oriented projects, which may be carried out in cooperation with participating local companies in the digital economy. These may include, for example, the development of a knowledge database, the creation of a target group analysis, optimization of current-state processes, cost–benefit analyses, lead generation on social media, or similar tasks.

Learning and qualification objectives: After successful participation in this project module, students are trained to organize and plan a practical business intelligence project, implement prototypical solutions, critically discuss the results, and present the applied methods and achieved outcomes in a structured project report.

Examination format: Project report (approx. 60%), presentation (approx. 40%); the exact grading weights will be announced at the beginning of the course. Each component must be passed individually. The overall grade is calculated as the weighted sum of the individual grades. Due to the changing project topics, components that have already been passed must be repeated if the module is retaken.

Further information

Contents: Work on selected research questions related to changing topics in the field of Business Informatics, particularly e-commerce; review of current research literature and, where applicable, implementation of (technical) solutions or conduct of empirical studies in small groups.

Learning and qualification objectives: After successful participation, students are able to:

• research, narrow down, understand, and analyze topic-related academic literature,
• structure their own findings in a meaningful way, present them in written form according to academic standards in a term paper, and present them orally,
• critically discuss academic research questions.

Examination format: Term paper (approx. 60%), presentation (approx. 30%), participation in discussions (approx. 10%); each component must be passed individually. The overall grade is calculated as the weighted sum of the individual grades. Due to the changing overarching seminar topics, components that have already been passed must be repeated if the seminar is retaken. Dates and the exact weighting of the components will be announced before the start of the course.

Further information

Contents: Disruptive technologies as drivers of digital transformation; business model innovations; digital platforms and their impact on traditional business models; platform strategy and governance mechanisms; the role of artificial intelligence and machine learning in business processes.

Learning and qualification objectives: After successful participation, students are able to

• identify disruptive technologies and assess their potential impact on existing business models and industry structures,
• analyze digital business models and transfer them to different industries based on their characteristics,
• understand the functioning and economic principles of digital platforms and evaluate their influence on traditional business models,
• develop strategies for the management and governance of digital platforms,
• recognize the relevance of artificial intelligence and machine learning for business processes and identify potential use cases.

Examination format: Project report and presentation in small groups (approx. 70%) and written examination during the examination period (approx. 30%). The exact weighting of the components in the overall grade will be announced at the beginning of the module. Both components must be passed individually. Participation in the written examination is therefore only possible if the project has been successfully completed. In the event of a possible retake of the written examination, the project performance will be credited.

Further information

Contents: Students are assigned practice-oriented projects, which may be carried out in cooperation with participating local companies in the digital economy. These may include, for example, the development of a knowledge database, the creation of a target group analysis, optimization of current-state processes, cost–benefit analyses, lead generation on social media, or similar tasks.

Learning and qualification objectives: After successful participation in this project module, students are trained to organize and plan a practical business intelligence project, implement prototypical solutions, critically discuss the results, and present the applied methods and achieved outcomes in a structured project report.

Examination format: Project report (approx. 60%), presentation (approx. 40%); the exact grading weights will be announced at the beginning of the course. Each component must be passed individually. The overall grade is calculated as the weighted sum of the individual grades. Due to the changing project topics, components that have already been passed must be repeated if the module is retaken.

Further information