Syllabus

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Applied Science University
Faculty: Economics and Administrative Sciences
Department : MIS Department
( Course Syllabus )
CourseTitle
Expert and Decision Support
Systems
Coordinator Name
I. Hadeel Abdellatif
Credit Hours
Course No.
3
408405
E-mail
[email protected]
Year (semester)
2012-2013 (1)
Office Hours
Posted on office door
Course Objectives:
The student, upon successful completion of the course, will have knowledge about the decision making process in
organizations, decision support system concepts and methodoligies, further, the course will introduce various data
warhousing and mining techniques, business intelligence and expert systems.
Course Description:
The course is devoted to introduce decision support systems and business intelligence; and covers the technologies
available to support individual and group decision making in organizations. This course covers the following
topics: Overview of decision support system, group decision support system, data warehousing and mining, data
visualization, business intelligence, expert systems, and state of the art technologies in the filed.
Intended Learning Outcomes :
Successful completion of this course should lead to the following learning outcomes :
A- Knowledge and Understanding :
A1) Understand the importance of decisoin making process.
A2) Understand the different methodologies to develop decision support systems.
A3) Understand the importance of business intelligence and expert systems.
B- Intellectual Skills:
B1) Be able to analyze different practical cases for different decision types.
B2) Be able to use different data mining techniques.
B3) Be able to demonestrate the relation between DSS and other information systems.
C- Subject Specific Skills:
C1) Use DSS software.
C2) Use expert system software.
C3) Analyze output of different data mining methodologies.
D- Transferable Skills:
D1) Work in a group in order to analyze cases and apply appropriate DSS and business intelligence.
D2) Work in a group in order to design DSS model for some case studies.
1
Course Contents :
No
Topics
Reference Chapter
Weeks
1
Decision Support System and Business
Intelligence Overview
Chapter 1
2
Decision making, Systems modeling and
suopport
Chapter 2
3
Decision Support Systems concepts, and
methodologies
Chapter 3
Week
4
Modeling and Analysis
Chapter 4
Week
5&6
Data mining for business intelligence
Chapter 5
Week
1
Week
2&3
4
5
Week
7&8
6
Artificial Nural networks for data mining
Week
9
Chapter 6
7
Chapter 7
Text & Web mining
8
9
Data Warehousing
Business Performance Management
Chapter 8
Chapter 9
10
Artificial Intelligence & Expert Systems
Chapter 12
11
Management Support Systems: Emerging
Trends & Impacts
Chapter 14
Week
10 & 11
Week 12
Week
13 & 14
Week
15
Week
16
Grade Distribution :
Assessment
Grade
- First Exam
- Second Exam
- Assignments ( Reports /Quizzes/ Seminar / Tutorials ….)
- Final Examination
Date
20%
20%
10%
50%
* Make-up exams will be offered for valid reasons. It may be different from regular exams in content and format.
Reading List:
Text Book
Other
References

Decision Support Systems and Intelligence Systems, Efraim Turban, Prentice Hall,9th
edition, 2011. website: www.prenhall.com/Turban.

Decision Support Systems In the 21st Century, George M. Marakas, Prentice Hall, 2nd
edition .

Decision Support System, V.S. Janakiraman, K. Saukesi, Prentice Hall of India, 2004.

Decision Support System and Data Warehouse Systems, Efrem Mallach,
McGrawHill, 2000.

http://dsscourses.com/tour, version 3.1, February 4, 2000.
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