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

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

Information Services and Electronic Markets > Studies

Participate

To sign up to this course, you must login.

Content

Important Information:

• Due to the dramatically worsening pandemic situation with an exponential increase in new infections, I decided our course will take place online. This course will be a combination of live tutorial sessions via Zoom and recorded videos for the lecture. All lecture and tutorial material, as well as the latest announcements, can be found in Ilias.
• All content and current information can be found in the Ilias course, accompanying literature here on our website.

Zoom Information for Tutorial:

Live Session: 29.11.2021

Join Zoom Meeting: https://kit-lecture.zoom.us/j/4478445656

Meeting ID: 447 844 5656

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.