Computer Programming for AI and Data Engineering

A collection of Python study notebooks, laboratory exercises, and practice problems covering core programming fundamentals and data engineering basics.

Overview

Part 1: Python Fundamentals (01-Python-Fundamentals/)

• Variables, operators, and basic data types
• String manipulation and text processing
• Data structures: Lists, Dictionaries, Sets, and Tuples
• Control statements and loop iterations
• Functions, variable scope, and lambda expressions
• List and dictionary comprehensions
• Object-oriented programming (OOP) basics
• Exception handling and file operations

Part 2: Laboratory Curriculum (02-Laboratory-Curriculum/)

• Hands-on programming exercises and problem-solving
• Algorithmic loop patterns and data transformations
• Sequence indexing and collection operations
• Dictionary structures and nested records
• Applied functions and practical Tkinter GUI examples
• Tabular data analysis and manipulation with Pandas

Getting Started

1. Clone the repository:

   git clone https://github.com/alperencok/Computer-Programming-for-AI-and-Data-Engineering.git
   cd Computer-Programming-for-AI-and-Data-Engineering

2. Install dependencies:

   pip install -r requirements.txt

3. Launch Jupyter:

   jupyter notebook

Author

• alperencok (https://github.com/alperencok)

License

This project is licensed under the MIT License.