The book can also be used to teach an advanced course on data mining, such as:
An introductory data mining course should use the materials in Chapters 1 to 7, which cover data preprocessing, data warehouse and OLAP technology, frequent pattern mining; classification and prediction, and cluster analysis. Chapter 4 may be omitted if you do not plan to cover implementation methods for data cubing and OLAP in depth. Alternatively, you may omit some sections in Chapters 1 to 7 and use Chapter 11 as final coverage of applications and trends in data mining.
An advanced course on data mining can use Chapters 8 through 11. These cover mining stream, time-series, and sequence data; graph mining, social network analysis, and multirelational data mining; mining object, spatial, multimedia, text, and Web data; and applications and trends in data mining. The text may be supplemented by research papers as well.
Individual chapters can be used for tutorials or for special topics in courses such as database systems, machine learning, pattern recognition, and intelligent data analysis.