Download Day 1 - Georgia Southwestern State University

Online CIS 6420 Data Mining
Department of Computer Science
Georgia Southwestern State University
Orientation
Maymester 2015
INSTRUCTOR
Name A. C. Shah
Office CWH Room 207
Office Phone 931 - 2114
e-mail [email protected]
Class Hours Online
Room CWH 221
Office Hours By email
TEXTBOOK
Title
Author(s)
Publisher
ISBN
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.
Title
Author(s)
Publisher
ISBN
Data Mining: Practical Machine Learning Tools and Techniques, 3rd
Edition Ian H. Witten and Eibe Frank
Morgan Kaufmann
978-0-12-374856-0
Download http://www.cs.waikato.ac.nz/~ml/weka/downloading.html
Weka
Windows x86 (for 32-bit OS)
Download a self-extracting executable that includes Java VM 1.7 (weka-3-610jre.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.
2.
3.
4.
apply methods of knowledge discovery in large databases
apply basic data mining concepts and techniques
investigate data patterns hidden in large data sets
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 May 11, 2015
Maymester ends May 28, 2015