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Isra University
1
Faculty Information Technology
Department of Computer Science
Course Plan
________________________________________________________________________________________________
Course No.:
601323
Course Name:
Data Mining
Course Website: www.elearn.isra.edu.jo
Course Classification:
Department Compulsory (CIS)
Time Division:
3 Lectures
Semester &Year: Second 2011/2012
Course Description
(3 credit hours, Prerequisite: 601322/ Data Warehouses)
Introduction to data mining, Input Concepts, Knowledge Representation, Decision Tables, Decision
Trees, Classification Rules, Association Rules, Data Mining Algorithms and Implementations in
Java.
Course Intended Outcomes
At the end of the course, students are expected to learn:
 Data Mining and Machine Learning Concepts and uses
 The different types of Data Mining techniques
 How to decide which technique to use with different problems
 How to implement Data mining methods in the Java Language
Course Outline
Week
1
2
3
ROOM: 4142
SUN/9:00-9:50
Introduction to Data Mining &
Course Outline
Data mining and machine
learning (Ch 1- Introduction)
Generalization as Search (Ch1)
Attributes (Ch 2)
ROOM: 4142
TUE/9:00-9:50
Data Warehousing – Review1
Simple Examples (Ch 1)
Concepts (Ch2 - Input)
Preparing the Input (Ch 2)
4
5
6
Decision Trees (Ch 3)
Rules with Exceptions (Ch 3)
Rules Involving Relations (Ch 3)
Review for First Exam
First Exam
(Th 24/11/2011)
7
8
9
Classification Rules (Ch 3)
Instance-based Representation
(Ch 3)
Statistical Modeling (Ch 4)
Clusters (Ch 3)
Constructing Decision Trees
(Ch 4)
10
Mining Association Rules (Ch 4)
Linear Models (Ch 4)
11
Review for Second Exam
Second Exam
(Tu 27/12/2011)
12
Training & Testing
Predicting performance
Cross-validation
(Ch5 - Credibility / Evaluating
what's been learned)
Other estimates
Comparing data mining Schemes
Predicting Probabilities (Ch 5)
13
Decision trees
Classification rules (Ch 6 -
Support vector machines
Instance-based Learning (Ch 6)
ROOM: 4142
THU/ 9:00-9:50
Data Warehousing –
Review2
Fielded Applications
(Ch 1)
Instances (Ch 2)
Decision tables ( Ch 3 –
Output / Knowledge
Representation )
Association Rules
(Ch 3)
Trees for Numeric
Prediction (Ch 3)
Return and Discussion
of
First Exam Results
Inferring rudimentary
(Ch 4 – Algorithms)
Constructing Rules
(Ch 4)
Instance-based
Learning (Ch 4)
Return and Discussion
of
Second Exam Results
Counting the cost
Evaluating numeric
prediction
The minimum
description length
principle (Ch 5)
Numeric prediction
Clustering (Ch 6)
Isra University
2
Faculty Information Technology
Department of Computer Science
Course Plan
________________________________________________________________________________________________
Implementation)
Exam Review
Third Exam
14
Exam Review
( TBA)
Final Exams
15
Textbook
Data Mining: Practical machine learning tools and techniques with Java implementation.
Ian Witten, Eibe Frank. Morgan Kaufmann, 3rd Ed.
Suggested references
1.
2.
3.
Data Mining, Adriaans, Zantige, Addison-Wesley, 1997.
Discovering data mining: From concepts to implementation, Cabena, Hadjinian, Prentice Hall, 1998.
Machine learning, Mitchell, McGraw Hill, 1997.
Marking
First Exam
Second Exam
Activity
Final Exam
25 marks
25 marks
10 marks
40 marks
Regulations
1.
2.
3.
4.
5.
There will be three term exams given during this semester. The best two out of three will be considered for
the First and Second Exam. This means: there will be NO makeup exams! Missing one of the two left
exams means a ZERO grade will be given for that exam.
There are no makeup for quizzes
Attendance is mandatory and University regulations will be enforced.
All Cheating incidents will be reported to the chair. The following activities are considered cheating:
a. Turning in assignment that includes parts of someone else's work.
b. Turning in someone else’s assignment as your own.
c. Giving assignment to someone else to turn in as their own.
d. Copying answers in a test or quiz.
e. Taking a test or quiz for someone else.
f. Having someone else take a test or quiz for you.
See Student handbook for other regulations.
Assignments and/or Projects
Assignments /
Description
Due Date
Marking
Quizzes
In each major section the students will be given assignments for practicing and
developing a good concept of the topic. Assignments’ deadlines and method of
delivery will be specified by instructors throughout the course.
Emailing Guidelines:
1.
2.
3.
4.
All homework, assignments, projects, etc., are sent by email to the email address shown below ( under
Instructor’s Information).
Be sure to send them before the due date.
Fill in the subject field of the email using the following format:
CIS201_Family-Name_First-Name_Subject , where:
a) CIS201 is abbreviation for the course. Other courses should have similar abbreviations
b) Family-Name and First-Name are replaced by your family name and your first name.
c) Subject is replaced by the title of the assignment, project, etc.
You may also use the email to ask questions about the course. In this case, just type the world “question” in
the place of _Subject as described in 3-c above.
Isra University
3
Faculty Information Technology
Department of Computer Science
Course Plan
________________________________________________________________________________________________
Required Tools/Software
 Java SE Development Kit (JDK 6 or higher) [ http://java.sun.com/javase ]
 TextPad 5.1 [ http://www.textpad.com ]
 Eclipse IDE for Java Developers [ http://www.eclipse.org/downloads ]
Instructor's Information
Lecture Room
: 4142
Lab
: 4319
Instructor's Name: Dr. Mohammad Ali H. Eljinini
Email: [email protected]
Section: 1
Office Hours:
Time:09:00-10:50 (SUN)
Time:09:00-10:50 (TUE/THR)
Office No.: 4106
Sun [11:00-12:00] Mon [09:00-10:00, 11:00-12:00]
Tue [1:00-2:00] Wed[ 10:00-11:00,12:00-1:00]
Other office hours are available by appointment
Important: The content of this syllabus may not be changed during the current semester
Instructor
Council Chair