Online CIS 6420 Data Mining
Department of Computer Science
Georgia Southwestern State University
Orientation
Maymester 2015

INSTRUCTOR

Name
Office
Office Phone
e-mail
Class Hours
Room
Office Hours / A. C. Shah
CWH Room 207
931 - 2114

Online
CWH 221
By email

TEXTBOOK

Title
Author(s)
Publisher
ISBN
Title
Author(s)
Publisher
ISBN
Download Weka / Data Mining – Concepts and Techniques, 2nd Ed (Textbook)
Jiawei Han and Micheline Kamber
Morgan Kaufmann
1-55860-901-6
Weka (Reference book) No need it buy this book.
Data Mining: Practical Machine Learning Tools and Techniques, 3rd Edition Ian H. Witten and Eibe Frank
Morgan Kaufmann
978-0-12-374856-0
http://www.cs.waikato.ac.nz/~ml/weka/downloading.html
Windows x86 (for 32-bit OS)
Download a self-extracting executable that includes Java VM 1.7 (weka-3-6-10jre.exe; 53.6 MB) OR
Windows x64 (for 64-bit OS)
Download a self-extracting executable that includes 64 bit Java VM 1.7 (weka-3-6-10jre-x64.exe; 55.1 MB)

REQUIREMENTS

You are expected to have following environment to progress smoothly and successfully in the course:
·  A laptop/desktop computer
·  Reliable Internet access using browsers such as Explorer 10.0 or Newest Firefox. For technical requirements, please go to this URL:
http://gsw.edu/Assets/GaVIEW/files/10.2/System_Software_Requirements.pdf
·  Microsoft Office (2007 or 2010 or 2013)
·  Access to the GeorgiaVIEW to go to the course resources.
·  You must have TEXTBOOK (mentioned above)
·  Storage Devices (optional): One 500 MB (or higher) USB Portable Storage Device
·  You must download and install data mining software Weka 3.6 that includes Java VM.

GAVIEW SUPPORT

The GAVIEW will be the platform for us to interact, post discussions, and send/receive emails. You will regularly login to GAVIEW to get course related information. Announcements will be made here. Reminder for Assignments, Quizzes, and Tests will be announced here. You will be able to chat with me.
Please note: Always logout after you are finished using GeorgiaVIEW and log off your computer after every virtual lab session (don’t leave your session sleeping for a long time).

CATALOG DESCRIPTION

CIS 6420 – Data Mining - This course is aimed at preparing students with a comprehensive look at the concepts and techniques needed to discover new knowledge from business data. It includes several methods of data mining, provides in-depth coverage of essential data mining topics including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis.(3-0-3) Prerequisites: ( CSCI 4400 Minimum Grade: C )

GOALS

To prepare the students with skills in data mining techniques and learn data mining tools such as Weka..

LEARNING OUTCOMES

Students completing this course should be able to:
1.  apply methods of knowledge discovery in large databases
2.  apply basic data mining concepts and techniques
3.  investigate data patterns hidden in large data sets
4.  distinguish the relationship between operational databases, data warehouse, and data mining
5.  apply proven algorithms/methods to derive information from large data sets.

Important Dates to Remember

Maymester begins
Maymester ends / May 11, 2015
May 28, 2015