ICT 6522: Data Warehousing and Mining

Announcement

• [13.08.16] Midterm 2 grade is updated; Max: 29, Average: 22.5
• [13.08.16] Term paper submission deadline extended to 04.09.16
• [31.07.16] Paper presentation schedule is available here
• [19.07.16] Midterm Exam 2 on 30.07.16 at 4 PM
• [12.07.16] Extra class on 16.07.16 is cancelled as I have exam duty during that time.
• [26.06.16] Midterm 1 grade is updated; Max: 30, Average: 20.3
• [26.06.16] No class on 29.06.16. Extra class on 16.07.16 from 3:30 PM.
• [22.06.16] Term Project description is available here
• [15.06.16] No class on 15.06.16
• [12.06.16] Guideline for Term Paper is available here
• [04.06.16] Class schedule during Ramadan: 4:00 PM to 5:30 PM
• [01.06.16] Term Paper Topic Selection deadline on 18.06.16. Email the topic.
• [01.06.16] Midterm Exam 1 on 08.06.16
• [24.05.16] No class on 25.05.16

Course Synopsis

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.

Reference Book

• 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.

Assessment

• Midterm Exam 1: 15%
• Midterm Exam 2: 15%
• Project: 10%
• Term Paper: 20%
• Final Exam: 40%

Class Lectures

• Lecture 1
• Lecture 2
• Lecture 3
• Lecture 4
• Lecture 5[Correction]
• Lecture 6
• Lecture 7
• Lecture 8
• Lecture 9
• Lecture 10

Projects

• Project Description