Organization (SoSe 25)
- Course
- 3+2 hours weekly (equals 6 ECTS)
- Lecture:
- Prof. Dr. Thomas Seidl
- Assistant:
- Philipp Jahn, Walid Durani
- Audience:
- Master or advanced Bachelor students in the programs of the Institute for Informatics
- Course Material:
- Moodle
- Prior Knowledge:
- Lecture "Data Mining Algorithmen I" or equivalent
- Course Language:
- English
Content
In many modern application areas, data scientists face challenges which go beyond the basic techniques being introduced in the basic course Data Mining Algorithms 1. The course on Data Mining Algorithms 2 covers advanced techniques to handle large data volumes, volatile data streams, complex object descriptions and linked data. These topics are also known as the three major challenges (Volume, Velocity, Variety) in Big Data Analysis. The module is directed at master students being interested in developing and designing knowledge discovery processes for various types of applications. This includes the development of new data mining and data preprocessing methods as well as the ability to select the best suited established approach for a given practical challenge.