Datenexploration und Systemmanagement mit Künstlicher Intelligenz / Maschinellem Lernen

After completion of the module, students will have an overview of the basic operations available for processing datasets measured in systems of any nature (e.g., physical, technical, biological, financial, etc.) and will be able to relate these operations to AI/ML-based methods and tools dedicated to a specific task. The students understand real world problems and can explain them using computer simulations. They know how to apply the acquired knowledge to an individual project, including increased skills in preparing project documentation and public presentation.

• Successful completion of the project task, 30 h
• Written examination, 90 min. OR
• Oral examination, 30-45 min. (with small number of participants)

• Hastie T., Tibshirani R., Friedman J.: The elements of statistical learning. Data mining, inference, and prediction. Springer, 2nd edition, New York 2009.
• Kulkarni S., Harman G.: Elementary introduction to statistical learning theory. Wiley & Sons Inc., New Jersey 2011.

Bewertungen von Studierenden

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