Rutgers University 3 credits Management Science and Information Systems
Introduction to data warehousing, mining, and knowledge management. The overall objective of this course is to introduce students to both technical and managerial issues and implications for business decisions of knowledge management, data mining, and data warehousing. Through lectures, discussions, and hands-on work, students learn to use as well as understand the strategic and effective application of these technologies. The knowledge discovery process includes data selection, cleaning, coding, using different statistical pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. Some topics covered include: knowledge discovery in databases, traditional statistics, neural networks, decision trees, Bayesian learning, association rules, commercial tools, feature selection, and advanced techniques. A special emphasis is made on the application domain of each method. Important related technologies such as data warehousing and Online Analytical Processing (OLAP) will be also discussed. Prerequisite: 29:623:319.
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