Course Instructor: Florin Rădulescu, Liviana Nicoleta Tudor

Syllabus:

This course presents technologies, methods and algorithms for Knowledge Discovery in Databases (KDD, also known as Data Mining).

The course presents various classes of problems and their specific algorithms: Data Preprocessing, Association Rules and Sequential Patterns, Supervised Learning, Unsupervised Learning, Partially Supervised Learning, Information Integration, Web Usage Mining.

The last part of the course contains an introduction in Data Warehousing and also describes some techniques for Dimensional Modeling and it use in storing data. Application hours target the understanding, presenting and testing some data mining algorithms, evaluation of their results for different datasets and different parameter values but also some case studies in Data warehousing.