Computer Science B565
|Class Days:||M, W|
|Days Per Week Offered:||Two.|
|Recommended follow-up classes:||CSCI-B555|
|Syllabus:||No Syllabus Avaliable|
|Keywords:||Prediction, clustering, association rule mining, data exploration, data visualization, anomaly detection.|
|Description:||The course objective is to study algorithmic and practical aspects of discovering patterns and relationships in large databases. This course is designed to introduce basic concepts of data mining and also provide hands-on experience in data analysis, clustering and prediction. Data mining is a dynamic field that has wide applications to a number of scientific areas such as finance, life sciences, social sciences, or medicine. This is a core Computer Science course.
The course covers about 75% of the following topics, depending on the year:
Data Mining: Concepts and Techniques - by J. Han et al., Morgan Kaufmann 2006.
Introduction to Data Mining - by P.-N. Tan et al., Pearson 2006.
|Formal Computing Lab:||No|
|Comments:||The course has several programming tasks.|