ICT 6522: Data Warehousing and Mining
Schedule: Sunday 5 PM to 8 PM
Office Hour: Sunday 3 PM - 4 PM
Please check latest announcments at MS Teams
This course introduces the concepts of Data warehouse, evolution of decision support system, Data warehouse environment, data model, design, Data warehouse technology, Data loading, clean up and transformation, Data cube and OLAP, Data mining introduction, classification, clustering, mining association rules, Data mining tools and applications, Data visualization, etc. The course prepares students to data mining algorithms and techniques. The course includes continuous assessment in the form of examinations.
- Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Pearson, 2005
- Krish Krishnan, Data Warehousing in the Age of Big Data, Morgan Kaufmann, 2013.
- MCQ(2): 10%
- Midterm Exam 1: 15%
- Midterm Exam 2: 15%
- Project and Term Paper: 20%
- Final Exam: 40%
All the lectures will be available at MS Teams.