Information Security Technology
Course Details

KTO KARATAY UNIVERSITY
Trade and Industry Vocational School
Programme of Information Security Technology
Course Details
Trade and Industry Vocational School
Programme of Information Security Technology
Course Details

| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 08131197 | Python Programming | 2025 | Autumn | 3 | 2+1+0 | 4 | 4 |
| Course Type | Elective |
| Course Cycle | Associate (Short Cycle) (TQF-HE: Level 5 / QF-EHEA: Short Cycle / EQF-LLL: Level 5) |
| Course Language | Turkish |
| Methods and Techniques | Project-Based Learning (PBL), Case Studies and Real-Life Examples |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Lect. Ayşe Merve BÜYÜKBAŞ |
| Instructor Assistant(s) | - |
Course Content
This course covers an introduction to the Python programming language, environment setup, basic operators, conditional statements and loops, and data structures (lists, tuples, sets, dictionaries). Error handling with try-except statements and file reading/writing operations are covered for reliable software development. Object-Oriented Programming (OOP) principles (classes, objects, inheritance, encapsulation, polymorphism) are taught through practical applications. Theoretical knowledge is put into practice through the use of standard Python libraries as well as external libraries (NumPy, Pandas, Matplotlib), creating custom modules, and reviewing the final project.
Objectives of the Course
The aim of this course is to equip students with the fundamental building blocks of the Python programming language, modern software development principles, and problem-solving approaches. The course aims to enable students to understand control flows, data structures, and modular functional programming logic; to apply object-oriented programming (OOP) principles; and to write reliable code using file management and debugging techniques. Furthermore, the use of standard and external libraries (NumPy, Pandas, Matplotlib, etc.) will provide students with a basic understanding of data processing and analysis processes.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to Python and Environment Setup |
| 2 | Basic Operators and Phrases |
| 3 | Control Flow - Conditions and Loops |
| 4 | Working with Collections (Lists, Bundles, Sets, Dictionaries) |
| 5 | Functions and Modular Programming (Function definition and calling, Function parameters and return values, Scope (local vs. global variables), Lambda functions, map, filter and list concepts) |
| 6 | Error Management and Debugging Techniques (Introduction to errors and error types; Error management with try, except, finally, and else; Debugging strategies and tools; Writing more robust code through error management) |
| 7 | General Review |
| 8 | Midterm Exam |
| 9 | Working with files (Reading from and writing to files, understanding file modes (read, write, append), working with file paths and file organization, basic error handling in file operations) |
| 10 | Introduction to Object-Oriented Programming (OOP) (Concepts of classes and objects, creating classes and constructors, working with properties and methods, the concept of 'self' and initializing object instances) |
| 11 | Advanced OOP Concepts (Inheritance and polymorphism, Encapsulation and private/public properties, Method overriding and super(), Creating basic projects using OOP) |
| 12 | Working with Libraries and Modules (Importing and using standard libraries (math, random, datetime, etc.), installing and using external libraries with pip, introduction to frequently used libraries: numpy, pandas, matplotlib, creating and importing custom modules) |
| 13 | General Review |
| 14 | Final Project and Review |
| 15 | Final Exam |
Textbook or Material
| Resources | Python for Beginners, by Ahmet Aksoy and Toygar Aksoy |
| Python Projects and Popular Libraries |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | 1 | 20 (%) |
| Seminar | - | - |
| Quiz | - | - |
| Listening | - | - |
| Midterms | 1 | 30 (%) |
| Final Exam | 1 | 50 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 4 | 56 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 1 | 14 |
| Midterms | 1 | 15 | 15 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 1 | 15 | 15 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 20 | 20 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 120 | ||
| Total Work Load / 30 | 4 | ||
| Course ECTS Credits: | 4 | ||
