USEFUL INFORMATION, RESOURCES & SERVICES FOR STUDENTSUSEFUL LINKS AND DOCUMENTS ADITIONAL & SUPPORTING INFORMATION

SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code	Course Name	Year	Semester	Theoretical	Practical	Credit	ECTS
50612METOZ-BLP0051	Programming Languages I	0	Spring	2	1	3	6

Course Type :
Cycle:	Associate TQF-HE:5. Master`s Degree QF-EHEA:Short Cycle EQF-LLL:5. Master`s Degree
Language of Instruction:	Turkish
Prerequisities and Co-requisities:	N/A
Mode of Delivery:	Face to face
Name of Coordinator:	Instructor STAFF
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SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives:

This course aims to teach students the fundamental principles of programming and enable them to apply practical skills such as algorithm development, data analysis, and automation using the Python language. By the end of the course, students are expected to understand basic Python commands and data structures, grasp the software development process, and be able to create their own projects.

Course Content:

The course will cover fundamental topics in Python, including basic syntax, data types, loops, conditional statements, functions, and modules. Additionally, students will be introduced to data structures such as lists, tuples, sets, and dictionaries, and will learn how to use these structures effectively. Various examples and practical exercises will be used to enhance programming logic, and basic file handling and error management will also be addressed. This course aims to develop students' problem-solving skills and prepare them for more advanced Python topics and other programming subjects.

Course Specific Rules

None

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:



Knowledge *(Described as Theoritical and/or Factual Knowledge.)*
1) Using Data Structures: Students will become familiar with Python data structures such as lists, tuples, sets, and dictionaries and will be able to perform data operations using these structures efficiently.
Skills *(Describe as Cognitive and/or Practical Skills.)*
1) Understanding Programming Fundamentals: Students will be able to develop simple programs using the basic syntax, data types, and basic commands of the Python language.
Competences *(Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)*
1) Implementing Conditional and Loop Structures: Students will be able to create algorithms by providing logical control flow with conditional statements and loop structures in Python.
2) Working with Functions and Modules: Students will be able to make their code more modular and reusable by using functions and modules.
3) Problem Solving and Error Management: Students will solve various programming problems and write robust programs using error management in Python.

Weekly Course Schedule

Week	Subject	Materials Sharing *
		Related Preparation	Further Study
1)	Introduction and Getting Started with Python Introduction to programming, * Features and areas of use of Python Installation of Python, * Introduction to IDE (PyCharm, Jupyter Notebook, etc.) * Basic Python commands and syntax	None Materyal	None Yoktur.
2)	Variables and Data Types Variable definition rules Numeric data types: integer (int), floating point (float), complex number Text data types: string (str) and character operations Conversions between data types	None	None.
3)	Basic Input/Output Operations and Receiving Data from the User * input() and print() functions * Formatting methods * Receiving data from the user and printing the output to the screen	None	None.
4)	Conditional Expressions if, elif, else structures Logical operators (==, !=, , =,	None	None.
5)	Loops - for and while Repeating operations with for loop While loop and break and continue commands *Solving sample problems with loops	None	None.
6)	Lists and Tuples Lists and list operations (addition, removal, sorting) Tuples and their uses *Examples and applications related to lists and tuples	None.	None.
7)	Midterm Exam	First 6 weeks lecture notes
8)	Sets and Dictionaries Sets and set operations Dictionaries and key-value structure Examples related to sets and dictionaries -- Functions - What is a function? Why is it used? Function definition and call Parameters, return value *Recursive functions	None	None.
9)	Functions - Lambda functions and anonymous functions map(), filter(), and reduce() functions *Applications and examples of functions	None	None.
10)	File Operations File opening, reading and writing operations File modes (r, w, a, r+ etc.) File closing and error handling Sample applications related to file operations	None.	None.
11)	Error Management and Exception Handling try, except, finally structures Error types and exceptions *Application development with error management	None.	None.
12)	Modules and Python Libraries Using pre-built Python modules (math, datetime, os, etc.) Creating and using your own modules *Installing third-party libraries (pip)	None.	None.
13)	Project Work and Applications Identify a simple Python project (e.g. calculator, small game, data analysis application)	None.	None
14)	Project Work and Applications Identify a simple Python project (e.g. calculator, small game, data analysis application)	None.	None.

*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Level of Contribution of the Course to PLOs

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Programme Learning Outcomes	Contribution Level (from 1 to 5)
1)	Gains the ability to develop software using the basic structures and algorithms of programming languages.
2)	Develop functional and sustainable software using object-oriented programming principles.
3)	Performs database design and management effectively, writes and implements SQL queries.
4)	Design dynamic and user-friendly web applications using web technologies and internet programming tools.
5)	Performs database design and management effectively, writes and implements SQL queries.
6)	Manages software development processes in accordance with professional ethical principles.
7)	Develop simple artificial intelligence applications in software projects with knowledge of artificial intelligence basics and Python programming.
8)	Applies database protection and defense methods in accordance with data security principles.
9)	Develops mobile applications at a basic level by understanding mobile application development processes.
10)	Design and implement appropriate software solutions by analyzing user needs.
11)	Performs basic network setup and management operations using network structures and protocols.
12)	Develop functional and aesthetic software applications using visual and user-oriented interface design principles.

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)

Teaching and Learning Methods defined at the Programme Level	Teaching and Learning Methods Defined for the Course
Lectures
Problem Solving
Demonstration
Laboratory
Individual and Group Work
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)

Aassessment and evaluation Methods defined at the Programme Level	Assessment and Evaluation Methods defined for the Course
Midterm
Final Exam
Quiz

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods	# of practice per semester	Level of Contribution
Quizzes	2	% 20.00
Midterms	1	% 30.00
Semester Final Exam	1	% 50.00
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
Total		% 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities	# of Activities per semester	Duration (hour)	Total Workload
Course	14	1	14
Laboratory	14	2	28
Application	0	0	0
Special Course Internship (Work Placement)	0	0	0
Field Work	0	0	0
Study Hours Out of Class	0	0	0
Presentations / Seminar	0	0	0
Project	7	6	42
Homework Assignments	0	0	0
Total Workload of Teaching & Learning Activities	-	-	84
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities	# of Activities per semester	Duration (hour)	Total Workload
Quizzes	2	20	40
Midterms	1	15	15
Semester Final Exam	1	20	20
Total Workload of Assesment & Evaluation Activities	-	-	75
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities)			159
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h)			6