SBWL Knowledge Management
Aim of course
Our goal is to share with students the significance of knowledge management in both soft and hard domains and empower them to apply the acquired knowledge to organizational practice. For this purpose, students are given plenty of opportunities for experimentation and exploration, which promotes their critical thinking and enhances their social competencies
Details About the Individual Courses
Course 1 – Knowledge-based Management (german)
In this course, students receive a comprehensive overview of knowledge-based management within a broad organizational context. Among other topics, the following questions are addressed:
- What is knowledge?
- Why is knowledge important?
- How can we generate and use knowledge?
- How does new knowledge emerge within organizations?
- How can knowledge be shared within organizations?
Course 2 – Semantic AI technologies for KM (english)
This course gives students an overview of Artificial Intelligence techniques in the context of KM. In particular, the basics of semantic knowledge representation technologies (taxonomie, ontologies, knowledge graphs) are taught.
Course 3 – Applications of Semantic AI in KM (english)
In this course the typical AI-based KM systems are illustrated in concrete use cases through data integration (manufacturing/smart city domain), search engines, chatbots and towards neuro-symbolic AI systems.
Course 4 – Organizational Learning (german)
In this course, we build upon the knowledge gained in Course 1 and apply Organizational Learning through a live case study. Students have the option to choose from varying and diverse emphases, with a strong focus on methods.
Course 5 – Research Seminar Knowledge Management (german/english)
In this course, students will be guided in creating a small academic paper in the field of Knowledge Management. They have the option to write this paper either more in the soft or hard domain.
For more information, you can read more about it here
