- Intermediate or advanced programming experience in any language (Python isa strong plus, but not mandatory) - English (spoken and written) - Ability and readiness to participate in oral exam activities according to the course schedule (online by Zoom)
Lectures, assignments, and an oral exam
More about the course content
The course provides an introduction to data mining and common applications, e.g. search engines, recommendation systems and text mining. It is a very practical course with many programming tasks and a practical project.
Other examples of topics are: The relationship between data mining and machine learning; Clustering algorithms, such as K-Means and Hierarchical Clustering; How to find similar things, e.g. documents and images; Analysis of links, e.g. PageRank; Dimension reduction, e.g. tSNE and PCA; Extracting information from text; Tools and program libraries for data mining.