CS 5710 - Data Mining of Scientific Data
Fall 2007- Course Syllabus
     (http://www.cs.appstate.edu/~rt/cs5710/f07/)


Professor: Dr. Rahman Tashakkori, e-mail:  rt@cs.appstate.edu, Web Page: http://www.cs.appstate.edu/~rt/
Office: CAP 121, Office Phone: 262-7009
Office Hours: MWF: 8:30-10:00 and MWF 12:00-1:00
Class Time/Location: MWF 12:00-12:50 /Room 444 CAP
Lab Location: Room 336 or 439 CAP
Final Exam:  Monday, December 10, 2007 from 9:00 AM - 11:30 AM 

Prerequisite 
Data Structures and Statistics (or permission of the instructor)

Textbook
Introduction to Data Mining, Rang-Ning Tan, Michael Steinbach, and Vipin Kumar, Addison Wesley, 2006 Edition.

Other References
Papers  from various resources
Handouts  provided  in class and online


Objective of the Course

Data mining plays an important role in knowledge discovery in large data sets.  It supports decision making by detecting patterns, devising rules, identifying new decision alternatives, and making predictions. Today, different experiments and studies produce significant amount of data that often contain valuable knowledge.  This course will introduce some basic knowledge discovery techniques that can be utilized for knowledge discovery in scientific data.  Students will learn about different types of data, data exploration, classification, and various knowledge discovery techniques. 

Tentative Course Outline
        Overview of Database Systems and Design
        Introduction to Data Mining and Knowledge Discovery
        Data
        Exploring Data
        Classification
        Association Analysis
        Current research in Knowledge Discovery and Data Mining
 
Individual Projects
All students are expected to conduct research project(s) and to write paper(s) individually.  

Grading policy
The following grading scale will be used in this course:
                        Exam One  20%,
                        Final exam, 30%,
                        Assignments 20%, and
                        Project(s) and presentations 30%

Students are required to attend all classes.   If you missed an exam due to an "extreme circumstances" such as illnesses, death of a relative, or problems of this nature, you have to present documents (e.g. a letter from a doctor, a letter from a hospital, or an obituary from the funeral).  In such cases, student's final exam's grade will be used for the missed exam.

Grading Scale
A = 93 to 100,  A- = 90-93.9
B+ = 87 to 89.9, B = 83-86.9, B- = 80-82.9
C+ = 77 to 79.9, C = 73-76.9, C- = 70-72.9
D+ = 67 to 69.9, D = 63-66.9, D- = 60-62.9
F = Below 60
No incomplete grade (I) will be given in this course.