The course provides an introduction to advanced data analysis techniques as a basis for analyzing business data and providing input for decision support systems. The course will cover the following topics:
The course consists of a lecture together with accompanying practical exercises as well as student team projects. In the exercises the participants will gather initial expertise in applying state of the art data mining tools on realistic data sets. The team projects take place in the last third of the term. Within the projects, students realize more sophisticated data mining projects of personal choice and report about the results of their projects in the form of a written report as well as an oral presentation.
The webpage about the HWS 2020 edition of this course is found in the lecture archive.
The review for the exam of FSS2021 will take place offline at the University in the week of July 12th. The exact place and time will be published here later. For attending the exam review you need to register via email with Alexander Brinkmann until Friday July 9th.
There is no second exam for FSS2021. The next opportunity to retake the project and exam is in HWS2021/
Note: there are three parallel exercise groups, you are supposed to attend only one.
Additional material will be found in the ILIAS group of the course.
Introduction to Data Mining
|10.03.2021||Lecture Clustering||Exercise Clustering|
|17.03.2021||Lecture Classification 1||Exercise Classification|
|24.03.2021||Lecture Classification 2||Exercise Classification|
|14.04.2021||Lecture Classification 3||Exercise Classification|
|21.04.2021||Video Lecture Regression||Exercise Regression|
|28.04.2021||Video Lecture Text Mining||Exercise Text Mining|
|5.05.2021||Video Lecture Association Analysis||Exercise Association Analysis|
|12.05.2021||Introduction to the Student Projects |
and Group Formation
|Preparation of Project Outlines|
|19.05.2021||Feedback on Project Outlines||Project Work|
|26.05.2021||Project Work||Feedback on demand|
|2.06.2021||Feedback on demand||Project Work|
|09.06.2021||Submission of project report (Deadline: 13.06)||Preparation of presentation|
|16.06.2021||Presentation of project results||Presentation of project results|
|23.06.2021||Final exam (online)|
For all students which are not familiar with Python/
Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar: Introduction to Data Mining, 2nd Global Edition, Pearson.
Vijay Kotu, Bala Deshpande: Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner. Morgan Kaufmann.
Aurélien Géron: Hands-On Machine Learning with Scikit-Learn and TensorFlow. O'Reilly.