YBS 406


Course Title Course Code Program Level
ARTIFICIAL INTELLIGENCE IN MANAGEMENT YBS 406 Management Information Systems B.A. / B.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
08
(Spring)
42 84 126 3 5

Teaching Staff
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites -
Recommended Optional Programme Component
Course Objectives This course is an introduction to artificial intelligence. Basic concepts will be examined in the context of computational intelligence. At the same time, efforts will be made to create a multidisciplinary awareness on artificial intelligence.
Course Content Basic concepts of artificial intelligence, machine learning, big data, expert systems, search and intelligent systems, and decision tree and artificial neural networks.
Learning Outcomes (LO) At the end of this course, students: Define artificial intelligence and its properties. Tells the areas of use Machine learning tells the areas of use of expert systems and decision trees.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Introduction, What is Artificial Intelligence? And what is Machine Learning?
2. Week Factors and environment
3. Week Knowledgeable search
4. Week Uninformed search
5. Week Games and Decision trees
6. Week Logic
7. Week Fuzzy Logic
8. Week Midterm Exam
9. Week Prolog
10. Week Machine Learning
11. Week Deep learning
12. Week Expert systems and Natural language processing
13. Week Artificial Neural Networks and Robotics
14. Week Application areas of artificial intelligence in businesses
Assessment
  Percentage(%)
Mid-term (%) 40
Quizes (%)
Homeworks/Term papers (%)
Practice (%)
Labs (%)
Projects/Field Work (%)
Seminars/Workshops (%)
Final (%) 60
Other (%)
Total(%) 100
Course Book (s) and/or References Doug Rose , Chicago.2018. Artificial Intelligence For Business Lakeshore Press
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)
 

PQ1

PQ2

PQ3

PQ4

PQ5

PQ6

PQ7

PQ8

PQ9

PQ10

PQ11

PQ12

PQ13

PQ14

LO1

5

 

3

2

 

2

5

 

 

 

 

 

 

 

LO2

5

 

 

 

 

 

 

 

 

 

 

2

 

 

LO3

5

 

 

 

 

 

 

 

1

 

 

 

 

 

 * Contribution Level : 1 Very low    2 Low     3 Medium     4 High      5 Very High