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| Detailed information |
| Pre-requisites |
(*)Erwartete Vorkenntnisse: Data Mining, Semantic Artificial Intelligence, Machine Learning: Supervised Techniques, Machine Learning: Unsupervised Techniques, Deep Learning and Neural Nets I, Probabilistic Models.
Hinweis: Diese Lehrveranstaltung darf nur bei Absolvierung des Studienschwerpunkts "Artificial Intelligence in Business" gewählt werden.
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| Original study plan |
Master's programme Business Informatics 2025W |
| Learning Outcomes |
Competences |
| Students are able to apply skills and knowledge of symbolic and non-symbolic methods of artificial intelligence (AI) acquired in the modules Data Mining, Semantic Artificial Intelligence, Machine Learning, Probabilistic Models, as well as Deep Learning and Neural Nets in operational case studies for the development of AI-based systems in various functional areas of business (marketing, finance & accounting, production & logistics, human resources) of Austrian and international companies.
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| Skills |
Knowledge |
- LO2: Students can participate in the development of an AI-based system as part of an interdisciplinary team to solve a practice-oriented problem (K5).
- LO3: They can create a requirements definition for an AI-based system in coordination with stakeholders (K4).
- LO4: They can independently acquire domain knowledge and technical know-how for the development of an AI-based system in a specific use case (K5).
- LO5: They can design partial solutions for AI-based systems and develop them based on a division of labor (K5).
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LO1: Analysis, design, implementation, introduction and/or evaluation of AI-based systems in the context of a practical project using symbolic and non-symbolic methods of AI in interaction with business, technical and social science approaches and taking into account important external factors such as legal standards and jurisdiction; methods and tools for the management of projects for the development of AI-based systems
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| Criteria for evaluation |
The course has an immanent examination character. The basis for assessment is the intensity and professionalism of participation, as well as the results achieved. The grading is based on the project results and the written project report as well as the ongoing presentations of intermediate and final results.
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| Language |
German/English |
| Changing subject? |
Yes |
| Further information |
This course may only be chosen if the major "Artificial Intelligence in Business" has been chosen.
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