Information Package / Course Catalogue
Robotics and Artificial Intelligence
Course Code: RYZ101
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 1
Credit: 3
Lab: 0
ECTS: 3
Objectives of the Course

The aim of the Robotics and Artificial Intelligence course is to provide students with basic knowledge and skills in these areas by teaching them the design, improvement, basic level programming, operation and installation of robotic systems used in industry, and the basic concepts and techniques in the field of artificial intelligence.

Course Content

The Robotics and Artificial Intelligence course aims to enable students to understand and maintain the functionality of robotic systems, to use artificial intelligence techniques to make these systems intelligent and autonomous, and to become equipped to meet future industrial and technological needs.

Name of Lecturer(s)
Learning Outcomes
1.Designs, prototypes and programs the basic components of robotic systems.
2.Understands the basic concepts and techniques in the field of artificial intelligence and performs data analysis and decision-making processes using methods such as machine learning and deep learning.
3.Develops software for the control and management of robotic systems using programming languages.
4.Analyzes complex problems and develops mathematical and algorithmic skills to solve them.
5.Develops new products, systems or services using robotics and artificial intelligence technologies.
Recommended or Required Reading
1.Robotics: Basic Concepts and Applications - Haluk Eren
2.Artificial Intelligence and Robotics: Ten Short Lessons (Pocket Einstein Series)-Peter J. Bentley
3.ROBOTICS AND ARTIFICIAL INTELLIGENCE: AN OVERVIEW OF ROBOT AND AUTOMATION TECHNOLOGY-Prasun Barua
4.Introduction to AI Robotics-Robin R. Murphy
Weekly Detailed Course Contents
Week 1 - Theoretical
Robotic System Components
Week 2 - Theoretical
Introduction to Artificial Intelligence
Week 3 - Theoretical
Robotics Kinematics - Forward Kinematics
Week 4 - Theoretical
Robotics Kinematics - Reverse Kinematics
Week 5 - Theoretical
Robotic Electronic - Basic Control Components
Week 6 - Theoretical
Robotics Electronics - Basic Control Components
Week 7 - Theoretical
Robotics Electronics - Basic Motion Components
Week 8 - Theoretical
Robotics Electronics - Basic Motion Components
Week 9 - Theoretical
Robotics Electronics - Basic Sensing Components
Week 10 - Theoretical
Robotics Electronics - Basic Sensing Components
Week 11 - Theoretical
Robotics and Artificial Intelligence Systems Development and Integration
Week 12 - Theoretical
Robotics and Artificial Intelligence Systems Development and Integration
Week 13 - Theoretical
Applications of Robotics and Artificial Intelligence Systems Development and Integration
Week 14 - Theoretical
Applications of Robotics and Artificial Intelligence Systems Development and Integration
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures10%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140114
Project1011
Studio Work5015
Individual Work100330
Quiz1011
Midterm Examination1011
Final Examination1011
TOTAL WORKLOAD (hours)81
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
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
OÇ-1
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
OÇ-2
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
OÇ-3
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
OÇ-4
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
OÇ-5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Adnan Menderes University - Information Package / Course Catalogue
2026