On successful completion of this Course, students will be able to: explain basic concepts of data mining; design and computation of data cubes; implement data processing and understand data modeling services; compare analysis techniques on data mining; implement analysis techniques in data mining; explain trends and applications associated with data mining.
- Data Warehousing, Data Generalization, and Online Analytical Processing;
- Data Preprocessing;
- Data Cube Computation and Data Generalization;
- Mining Frequent Patterns, Association, and Correlations;
- Classification and Prediction;
- Cluster Analysis;
- Graph Mining, Social Network Analysis, and Multirelational Data Mining;
- Implementations: Real machine learning schemes;
- Applications and Trends in Data Mining;
- The Weka machine learning workbench.
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