An Introduction to Data Warehousing and Data Mining (English)

Description:	About the Course As an introductory course for data warehouse and data mining, this course introduces the concepts, algorithms, techniques, and systems of data warehousing and data mining, including (1) design and implementation of data warehouse and OLAP systems; and (2) data mining concepts, methods, systems, implementations and applications. The course will serve mainly CS senior-level undergraduate students and the first year graduate students interested in the field. Also, the course may attract students from other disciplines who need to implement and/or use data warehouse and data mining systems to analyze large amounts of data. Prerequisites Background: CS 225 or CS 300 or consent of instructor (good statistics and machine learning knowledge will help understanding the course materials). Programming: For our programming projects, you will need to have familiarity with Linux and languages such as C++, or Java. We will not cover programming-specific issues in this course.
Lecturer:	Han, Jiawei
Language:	English
URL:	http://www-courses.cs.uiuc.edu/~cs498han/
Material Url:	http://www-sal.cs.uiuc.edu/~hanj/DM_Book.html
Date:	2004
Topics:	Data Mining
Publications:	Hastie/etal/2001a: The Elements of Statistical Learning: Data Mining, Inference, and Prediction Mitchell/97b: Machine Learning Witten/Frank/2000b: Data Mining -- Practical Machine Learning Tools and Techniques with Java Implementations

About the Course