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Course ID:IT608
Course: Data Warehousing and Data Mining
Instuctor: Dr. Sunita Sarawagi
Prerequesites: IT623, An undergraduate course in database systems is helpful
Contents:
  • Basic data warehouse architecture, data consolidation, warehouse internals: storage and indexing, materialized views and aggregate precomputation. Online analytical Processing (OLAP) systems. Data Mining: main operations: clustering, classification, regression, neural networks, feature selection, deviation detection, item set associations, discoveries along time, similarity of complex objects. System integration issues in decision support tools. Survey of existing mining and OLAP products, success and failure stories of data mining: 
  • References::
  • Machine Learning. McGraw-Hill, 1997:  T. Mitchell
  • Mannila Principles of Data mining:  Hand, Smyth
  • Data Mining: Concepts and Techniques:  Jiawei Han, Micheline Kamber, Morgan Kaufmann Publishers
  • Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press, 1996:  Usama M. Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth, and Ramasamy Uthurusamy
  • Selected papers from conferences and journals, conference tutorials: 




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