Course Name Code Semester T+U Hours Credit ECTS
Business Intelligence YBS 510 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi HALİL İBRAHİM CEBECİ
Course Lecturers Dr.Öğr.Üyesi HALİL İBRAHİM CEBECİ,
Course Assistants
Course Category
Course Objective 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
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Intelligent systems and analysis on its importance Lecture, Question-Answer, Discussion, Drilland Practice, Self Study, Problem Solving, Testing, Homework,
2 Criticising the kinds of intelligent systems and evaluating with comparison Lecture, Question-Answer, Drilland Practice, Self Study, Problem Solving, Testing, Homework,
3 Introduction , definition, depiction and comparison of the concepts of intelligent systems and Technologies from the enterprise perspective Lecture, Question-Answer, Discussion, Drilland Practice, Testing, Homework,
4 Criticising the differences between intelligent and information systems and detecting the patterns Lecture, Question-Answer, Discussion, Drilland Practice, Self Study, Problem Solving, Testing, Homework,
5 Database design and creation Lecture, Question-Answer, Discussion, Drilland Practice, Self Study, Problem Solving, Testing, Homework,
6 Analysis on the applications of intelligent systems to business environment , criticising in accordance with the criteria and providing solutions. Lecture, Question-Answer, Discussion, Drilland Practice, Self Study, Problem Solving, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Introduction to Artificial Intelligence and basic concepts: What is Artificial Intelligence?
2 The concept of natural and artificial intelligence and Decision Support Sytems
3 The features of intelligent systems and intelligent decision support systems
4 The basic components of intelligent decision support system
5 Expert systems-1
6 Fuzzy logic
7 Decision Support Systems
8 MID TERM EXAM
9 Learning
10 Artificial Neural Networks-1
11 Artificial Neural Networks-2
12 Genetic Algorithms
13 Other biologic heuristic techniques
14 Intelligent agents
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Can use next generation computing-based business analytics techniques and apply these methods to business problems
2 Offers developed solutions with information technologies such as Business Intelligence tools
3 Makes the routine decisions necessary for the execution of operational works with the help of information technologies.
4 Makes medium and long term strategic decisions with the help of information systems.
5 Can transform business processes into electronic form with the help of information systems
6 Contributes to the sustainability of processes with electronic transformation.
7 Makes a basic literature search on the field.
8 Knows about research methodology and applies this knowledge to informatics issues.
9 Leading the working group by communicating within the team in teamwork.
10 Effectively uses group communication technologies in IT projects management.
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Ödev 15
2. Ödev 15
3. Ödev 20
Total 100
1. Yıl İçinin Başarıya 60
1. Final 40
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 5 80
Mid-terms 1 5 5
Quiz 2 3 6
Final examination 1 5 5
Total Workload 144
Total Workload / 25 (Hours) 5.76
dersAKTSKredisi 6