People Innovation Excellence
 

Knowledge Data Discovery

Learning Outcomes

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.

Topics

  1. Introduction;
  2. Data Warehousing, Data Generalization, and Online Analytical Processing;
  3. Data Preprocessing;
  4. Data Cube Computation and Data Generalization;
  5. Mining Frequent Patterns, Association, and Correlations;
  6. Classification and Prediction;
  7. Cluster Analysis;
  8. Graph Mining, Social Network Analysis, and Multirelational Data Mining;
  9. Implementations: Real machine learning schemes;
  10. Applications and Trends in Data Mining;
  11. The Weka machine learning workbench.

 


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