Objectives: Students will be enabled to understand and
implement classical models and algorithms in data warehousing and data
mining. They will learn how to analyze the data, identify the
problems, and choose the relevant models and algorithms to apply.
They will further be able to assess the strengths and weaknesses of
various methods and algorithms and to analyze their behavior.
Syllabus
- Data warehousing
- SQL OLAP extensions
- Multi-dimensional Join
- Data warehouse performance
- Data Analysis and Uncertainty
- Classification and Prediction
- Cluster Analysis
- Association rules
The course organization is divided in two parts that are thaught in parallel: a data warehousing part and a data mining part. The exercises consist in doing a project alone or in groups of 2-3 students (more details below). Textbooks
