Syllabus

CS522 Advanced Database Systems

Winter 2012
Computer Science Department
California State University, Los Angeles


Lectures:
 Tuesday and Thursday 11:40am - 1:20pm, in E&T A210
Instructor:
 Chengyu Sun
Email: csun@calstatela.edu
Office: E&T A317
Office Hours: M 4-6pm, T 1:30-3:30pm, and R 3-5pm, or by appointment, in E&T A317
Course Description:
This is an introductory course on data mining. We will cover concepts, algorithms, and applications in data warehousing and OLAP, mining frequent patterns and association rules, classification and predication, and cluster analysis.
Prerequisites:
 CS422 and CS491/CS496
Textbook(s): Data Mining: Concepts and Techniques, by Jiawei Han and Micheline Kamber
Optional: Introduction to Data Mining, by Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Software Tools:
 Required - Email
Optional (for access online lecture notes) - Adobe Acroread and/or MS PowerPoint
Grading Policy:
 Homeworks and Projects 40%, Quizzes 10%,  Midterm 25%, Final 25%

90 - 100
80 - 90
60 - 80
40 - 60
below 40 		A
B
C
D
F
Tentative Schedule:
Week
 Topics
 Chapters
1
 Administrative issues
Course Overview
Data Warehouse and OLAP
1
3
2 Data Cube Computation 4.1-4.2
3-4
 Frequent Patterns
 5
5-6
 Classification
 6
7
 MIDTERM
8-9
 Clustering
 7
10
 Anomaly Detection
 7
11
 FINAL
Online Resources:
Academic Integrity:
 Cheating will not be tolerated. Cheating on any assignment or exam will be taken seriously.  All parties involved will receive a grade of F for the course and be reported to the Academic Senate.