MA-WW-WINF-0416 - Data Science: Advanced Analytics
| Chair | Business Information Systems, esp. Intelligent Systems and Services | |
| Lecturer | Prof. Dr. Benedikt Brendel | |
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Objectives & Content |
The module deals with the basics of unsupervised methods for finding patterns in structured and unstructured data. Students lern methods from the field of machine learning using analytical information systems. Students are able to apply these methods to various practical examples and to evaluate, interpret and critically question the results. Students are able to analyse unstructured data using text mining methods. The students have an understanding of problems that can occur in the course of the knowledge-discovery-in-databases process and are able to ecognize and solve these problems. Furthermore, the students have knowledge of special procedures in the context of specific application scenarios of machine learning, such as process analysis (process mining) and anomaly detection. They have the ability to design and implement solutions to problems on the basis of structured and unstructured data with selected application systems of machine learning | |
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Forms of Teaching & Learning |
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| Frequency | Every summer semester | |
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Further information |
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