Information Package / Course Catalogue
Artificial Intelligence Applications I
Course Code: YZO102
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 1
Credit: 4
Lab: 0
ECTS: 5
Objectives of the Course

This course introduces students to advanced features and concepts of the Python programming language. Students will further develop their software development skills by learning topics such as loops, functions, dictionaries, file management, error handling, and database operations. Throughout the course, they will have the opportunity to reinforce their theoretical knowledge with various example applications.

Course Content

Loops, functions, dictionaries, file management, error handling and database operations, projects and applications

Name of Lecturer(s)
Ins. Ümit BULUT
Learning Outcomes
1.Learn the fundamentals and building blocks of the Python programming language.
2.Recognizes what can be done with Python and the application areas of this language.
3.Develops programs with functions and modules in Python.
4.Recognizes the types of problems encountered in artificial learning and produces solutions.
5.Have knowledge about types of artificial learning (supervised, unsupervised, semi-supervised, reinforcement learning).
Recommended or Required Reading
1.Python and Artificial Intelligence with Applications, Emrah Aydemir, June, 2023, Nobel Academic Publishing.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Python
Week 2 - Theoretical
Python Conditional Structures
Week 3 - Theoretical
Loops (While Loop)
Week 4 - Theoretical
Loops (For Loop)
Week 5 - Theoretical
General Review and Problem Solving
Week 6 - Theoretical
Python Functions
Week 7 - Theoretical
Python Dictionaries
Week 8 - Theoretical
Python Error Handling (Try-Except) (Midterm Exam)
Week 9 - Theoretical
Python File Management
Week 10 - Theoretical
Python Database Operations
Week 11 - Theoretical
Artificial Intelligence Concepts
Week 12 - Theoretical
Types of Machine Learning
Week 13 - Theoretical
Artificial Learning Stages
Week 14 - Theoretical
Machine Learning Libraries
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142370
Lecture - Practice141128
Project51215
Midterm Examination1516
Final Examination1516
TOTAL WORKLOAD (hours)125
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
OÇ-1
5
5
4
4
5
3
5
4
5
5
4
5
OÇ-2
4
5
4
5
4
5
4
2
4
4
5
5
OÇ-3
3
3
3
4
4
4
3
2
4
5
4
3
OÇ-4
3
3
3
4
4
4
5
3
4
2
5
3
OÇ-5
4
5
4
5
4
5
3
4
5
3
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026