Information Package / Course Catalogue
Business Intelligence
Course Code: MIS529
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 7
Objectives of the Course

Is to introduce the methods benefited in intelligent system applications

Course Content

Introduction To Artificial Intelligence, Natural-Artificial İntelligence, Expert Systems, Learning, Artificial Neural Networks, Genetic Algorithms, Fuzzy Logic, İnteligent Agents

Name of Lecturer(s)
Learning Outcomes
1. Intelligent systems and analysis on its importance
2.Criticising the kinds of intelligent systems and evaluating with comparison
3.Introduction , definition, depiction and comparison of the concepts of intelligent systems and Technologies from the enterprise perspective
4.Criticising the differences between intelligent and information systems and detecting the patterns
5.Database design and creation
6.Analysis on the applications of intelligent systems to business environment , criticising in accordance with the criteria and providing solutions.
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Artificial Intelligence and basic concepts: What is Artificial Intelligence?
Week 2 - Theoretical
The concept of natural and artificial intelligence and Decision Support Sytems
Week 3 - Theoretical
The features of intelligent systems and intelligent decision support systems
Week 4 - Theoretical
The basic components of intelligent decision support system
Week 5 - Theoretical
Expert systems-1
Week 6 - Theoretical
Fuzzy logic
Week 7 - Theoretical
Decision Support Systems
Week 8 - Intermediate Exam
Midterm
Week 9 - Theoretical
Learning
Week 10 - Theoretical
Artificial Neural Networks-1
Week 11 - Theoretical
Artificial Neural Networks-2
Week 12 - Theoretical
Genetic Algorithms
Week 13 - Theoretical
Other biologic heuristic techniques
Week 14 - Theoretical
Intelligent agents
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory163396
Individual Work161364
Midterm Examination1156
Final Examination19514
TOTAL WORKLOAD (hours)180
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
4
5
5
5
5
5
5
5
4
OÇ-2
5
5
4
4
5
5
5
5
5
OÇ-3
4
4
4
4
4
3
3
3
3
OÇ-4
4
4
4
4
4
4
3
3
4
OÇ-5
4
4
4
4
4
4
4
5
5
OÇ-6
5
5
4
3
3
3
4
4
4
5
Adnan Menderes University - Information Package / Course Catalogue