BIM 439 - Data Mining

Course Learning Outcomes

1. Identify the fundamental steps of knowledge discovery and data analysis processes, analyze data using appropriate algorithms, and evaluate the results.
2. Perform data cleaning, data integration and transformation, data reduction, and feature extraction.
3. Develop data mining models such as classification, clustering, and regression, and apply them to datasets by selecting suitable methods.
4. Apply data mining techniques (e.g., classification, clustering, association rules) to various fields such as marketing, healthcare, and finance, and evaluate the significance of these rules.
5. Present results using comprehensible visuals and reports, and explain findings to relevant stakeholders.

ECTS / Workload

Course Schedule