AIE504 Machine Learning Istanbul Okan UniversityDegree Programs PhD in Mechatronic Engineering (English) with a bachelor's degreeGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
PhD in Mechatronic Engineering (English) with a bachelor's degree
PhD TR-NQF-HE: Level 8 QF-EHEA: Third Cycle EQF-LLL: Level 8

General course introduction information

Course Code: AIE504
Course Name: Machine Learning
Course Semester: Spring
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 10
Language of instruction: EN
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: Department Elective
Course Level:
PhD TR-NQF-HE:8. Master`s Degree QF-EHEA:Third Cycle EQF-LLL:8. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. BEKİR TEVFİK AKGÜN
Course Lecturer(s): Dr.Öğr.Üyesi SİNA ALP
Course Assistants:

Course Objective and Content

Course Objectives: A. Explaining the Elective Course Topic
B. Using Elective Course Methods / Tools
C. To produce solutions in Elective Course.
Course Content: History of games and current game trends. Basics of game design and development. Basics of game design. Simulation creation. The use of artificial intelligence in games. The place of physics and mathematics in games. Computer graphics concepts used in games. Human computer interaction in game development.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) A. Explains Elective Course Subject.
2) B. Uses Elective Course Methods / Tools.
2 - Skills
Cognitive - Practical
1) C. Elective Course produces solutions.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) History of games and current game trends Course Notes
2) Basics of game design and development Course Notes
3) Basics of game design and development Course Notes
4) Basics of game design Course notes
5) Creating simulation Course notes
6) Midterm Course notes
7) The use of artificial intelligence in games Course notes
8) The use of artificial intelligence in games Course notes
9) The place of physics and mathematics in games Course Notes
10) Computer graphics concepts used in games Course notes
11) Computer graphics concepts used in games Course notes
12) Human computer interaction in game development Course notes
13) Midterm Course note
14) Human computer interaction in game development Course notes
15) Final Exam Course Notes

Sources

Course Notes / Textbooks: Ders notları
References: Course Notes

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

3

Program Outcomes
1) Knowledge and ability to apply the interdisciplinary synergetic approach of mechatronics to the solution of engineering problems
2) Ability to design mechatronic products and systems using the mechatronics approach
3) Knowledge and ability to analyze and develop existing products or processes with a mechatronics approach
4) Ability to communicate effectively and teamwork with other disciplines
5) Understanding of performing engineering in accordance with ethical principles
6) Understanding of using technology with awareness of local and global socioeconomic impacts
7) Approach to knowing and fulfilling the necessity of lifelong learning

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Knowledge and ability to apply the interdisciplinary synergetic approach of mechatronics to the solution of engineering problems
2) Ability to design mechatronic products and systems using the mechatronics approach
3) Knowledge and ability to analyze and develop existing products or processes with a mechatronics approach 2
4) Ability to communicate effectively and teamwork with other disciplines
5) Understanding of performing engineering in accordance with ethical principles
6) Understanding of using technology with awareness of local and global socioeconomic impacts
7) Approach to knowing and fulfilling the necessity of lifelong learning

Learning Activity and Teaching Methods

Expression
Brainstorming/ Six tihnking hats
Individual study and homework
Q&A / Discussion

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Midterms 2 % 40
Final 1 % 60
total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 15 3 45
Midterms 2 70 140
Final 1 100 100
Total Workload 285