Akademik Dersler - İçerik

Weeks	Topics
Week - 1	Introduction to Programming: What is an algorithm, why is it important, explanation with real-life examples. Installing Python. Preparing the work environment. Simple “Hello Python” example.
Week - 2	Basic Data Types and Operators: Introduction to int, float, string, and boolean data types. Type conversions. Explanation of arithmetic, comparison, and logical operators with practical examples.
Week - 3	Conditional Statements: Establishing the program's decision-making mechanism with if-else structures. Complex conditions using comparison and logical operators. Nested conditions. Mini applications.
Week - 4	Loops I: Repeating operations with for and while loops. Example applications.
Week - 5	Loops II: Using range, enumerate, break, and continue. Example applications.
Week - 6	Data Structures: Lists, tuples. Basic operations: insertion, deletion, sorting, slicing. Application areas and performance differences. Dictionaries (dict) and nested data structures. Key-value logic.
Week - 7	General Methods: Mathematical methods and chain methods. Examples of use.
Week - 8	Functions: Function definition, parameters, and return values. Default parameters. Calling by value and by reference. Examples of real-life function applications.
Week - 9	File Operations: Opening/reading/writing files (txt, CSV). Secure file operations using the with statement. Reading and writing data from CSV files.
Week - 10	Errors and Exceptions: try-except structure, multiple except blocks. finally block. Custom error messages. Real-life example: Catching errors when a file cannot be found.
Week - 11	Introduction to Object-Oriented Programming: The concepts of class and object. Method, property, inheritance. Encapsulation and its advantages. Small example: Defining a Student class.
Week - 12	Modules and Libraries: Standard libraries (math, random, datetime). Package management with pip. Third-party library installation and simple usage examples.
Week - 13	Python Libraries for Data Analysis: Arrays and basic operations with NumPy. Creating DataFrames, reading and filtering data with Pandas. Simple graphing with Matplotlib.
Week - 14	A Small Project Data Analysis: Reading, cleaning, analyzing, and presenting data with graphs on a real data set (e.g., traffic or weather data).