Information Services and Electronic Markets
Prof. Dr. Andreas Geyer-Schulz | Schroff-Stiftungslehrstuhl

Institute of Information Systems and Marketing
Department of Economics and Business Engineering

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Informationsdienste und elektronische Märkte
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Content

All lecture and tutorial material, as well as the latest annoucements, can be found in the corresponding ILIAS course. Further literature is referenced on this website.

Course Description:

In recent years, the volume, variety, velocity, veracity, and variability of available data have increased due to improvements in computational and storage power. The rise of the Internet has made available large sets of data that allow us to use and merge them for different purposes. Data science helps us to extract knowledge from the continually-increasing large datasets. This course will introduce students to a wide range of machine learning and statistical techniques. Students will learn theory and concepts with real data sets from different disciplines such as finance, marketing, and business.

Literature:

• Alpaydin, E. (2014). Introduction to Machine Learning. Third Edition, MIT Press.
• Hall, J. (2020). Machine Learning in Business: An Introduction to the World of Data Science. Independently published.
• James, G., Witten, D., Hastie, T., and R. Tibshirani (2013). An Introduction to Statistical Learning: with Applications in R. Springer.
• Tan, P. N., Steinbach, M., Karpatne, A., & Kumar, V. (2018). Introduction to data mining. Pearson.