Algoritmos II 📚

Welcome to the Algoritmos II repository! This space contains the code, exercises, and practical work from the Algorithms and Programming II course. Here, we focus on essential data structure concepts and sorting methods, emphasizing efficient algorithm implementation and complexity analysis.

Table of Contents

• Introduction
• Course Overview
• Topics Covered
• Repository Structure
• How to Use
• Contributing
• License
• Contact

Introduction

This repository serves as a practical resource for students and enthusiasts of algorithms. It includes various examples, exercises, and implementations that support the learning of fundamental concepts in algorithms and data structures.

The course covers important topics such as sorting algorithms, complexity analysis, and data structures like hash tables and heaps.

Course Overview

The Algorithms and Programming II course aims to deepen your understanding of algorithmic principles. You will learn to implement efficient algorithms and analyze their performance. The course emphasizes hands-on practice through coding exercises and projects.

Key Learning Objectives

• Understand various sorting algorithms and their applications.
• Analyze the complexity of algorithms using Big O notation.
• Implement data structures such as hash tables and heaps.
• Develop problem-solving skills through practical coding exercises.

Topics Covered

This repository includes materials on the following topics:

• Big O Notation: Understand how to analyze the performance of algorithms.
• Sorting Algorithms: Learn about different sorting methods, including:
  • Bubble Sort
  • Insertion Sort
  • Selection Sort
  • Merge Sort
  • Quick Sort
  • Heap Sort
  • Tim Sort
• Data Structures: Explore the implementation and usage of hash tables and heaps.

Repository Structure

The repository is organized into several folders and files, each dedicated to a specific topic. Here’s a brief overview of the structure:

AlgoritmosII-Faculdade/
│
├── bubble-sort/
│   ├── bubble_sort.py
│   ├── README.md
│
├── insertion-sort/
│   ├── insertion_sort.py
│   ├── README.md
│
├── selection-sort/
│   ├── selection_sort.py
│   ├── README.md
│
├── merge-sort/
│   ├── merge_sort.py
│   ├── README.md
│
├── quick-sort/
│   ├── quick_sort.py
│   ├── README.md
│
├── heap-sort/
│   ├── heap_sort.py
│   ├── README.md
│
├── hash-table/
│   ├── hash_table.py
│   ├── README.md
│
├── complexity-analysis/
│   ├── complexity_analysis.py
│   ├── README.md
│
└── README.md

Each sorting algorithm folder contains a Python implementation and a README file explaining the algorithm and its complexity.

How to Use

To get started with the code in this repository, follow these steps:

1. Clone the Repository: Use the following command to clone the repository to your local machine.

   git clone https://github.com/GSchallK/AlgoritmosII-Faculdade.git

2. Navigate to the Desired Folder: Change to the directory of the algorithm you want to explore. For example:

   cd AlgoritmosII-Faculdade/bubble-sort

3. Run the Code: Execute the Python file to see the algorithm in action.

   python bubble_sort.py

4. Explore the README Files: Each folder contains a README file that provides an overview of the algorithm, its implementation, and its complexity analysis.

For downloadable releases, check the Releases section.

Contributing

Contributions are welcome! If you have suggestions or improvements, feel free to fork the repository and submit a pull request.

To contribute:

1. Fork the repository.
2. Create a new branch for your feature or fix.
3. Make your changes and commit them.
4. Push to your forked repository.
5. Submit a pull request.

License

This repository is licensed under the MIT License. See the LICENSE file for more details.

Contact

For any questions or feedback, please reach out to me at [your_email@example.com].

Thank you for visiting the Algoritmos II repository! We hope you find these resources helpful in your learning journey.

Remember to check the Releases section for downloadable content and updates. Happy coding!