IST565 Data Mining
Fall 2015 Syllabus
Updated 08/27/2015
Instructor: Professor Bei Yu | Classroom: Hinds 013 |
Email: byu.teaching@gmail.com | Class sections: Tue, Wed |
Office: Hinds 320 | TA: TBD |
Office hour: TBD | TA Office hour: TBD |
I. Course Description and Objectives
This course will introduce popular data mining methods for extracting knowledge from data. The principles and theories of data mining methods will be discussed and will be related to the issues in applying data mining to problems. Students will also acquire hands-on experience using state-of-the-art software to develop data mining solutions to scientific and business problems. The focus of this course is in understanding data and how to formulate data mining tasks in order to solve problems using the data.
The topics of the course will include the key tasks of data mining, including data preparation, concept description, association rule mining, classification, clustering, evaluation and analysis. Through the exploration of the concepts and techniques of data mining and practical exercises, students will develop skills that can be applied to business, science or other organizational problems.
The format of the class meetings will be a combined lecture and lab format, with lectures and class discussions to cover material and lab time to investigate small examples for the topic of the week. There will be weekly readings based on the textbook and on other materials which will be posted on-line.
Upon completion of this course, students are expected to be able to:
* Understand the fundamental processes, concepts and techniques of data mining,
* Develop familiarity with data mining techniques and be able to apply them to real-world problems,
* Advance your understanding of contemporary data-mining systems.
II. Course Materials
Required textbook
Pang-Ning Tan, Michael Steinbach, and Vipin Kumar (2005) Introduction to Data Mining. (Free sample...
