Welcome to the Linkedin_List_Interview_Questions 2024 repository! This repository is a collection of common interview questions that you might encounter during technical interviews, specifically tailored for LinkedIn interviews in the year 2024. It also includes code solutions and explanations to help you prepare effectively.
Technical interviews can be challenging, and preparation is key to success. The Linkedin_List_Interview_Questions 2024 repository is here to assist you in your preparation for LinkedIn technical interviews. It includes a wide range of interview questions covering various topics such as data structures, algorithms, system design, and more.
This repository provides:
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Interview Questions: A curated list of interview questions commonly asked in LinkedIn interviews in 2024. The questions are categorized by topics for easy navigation.
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Code Solutions: Detailed code solutions for each interview question, along with explanations. These solutions are designed to help you understand the problem-solving process and improve your coding skills.
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Contributions: You are encouraged to contribute by adding new questions, improving existing solutions, or suggesting enhancements. This collaborative effort can make this repository even more valuable for interview candidates.
To get started with this repository, follow these steps:
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Clone the Repository: Clone this repository to your local machine using Git.
git clone https://github.com/yourusername/Linkedin_List_Interview_Questions_2024.git -
Navigate to a Question: Browse the repository to find a specific interview question you want to practice.
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Read the Question: Open the question's markdown file to read the problem statement and any additional information provided.
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Study the Solution: Review the code solution and explanation to understand the approach used to solve the problem.
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Contribute: If you have an improvement or want to add a new question, feel free to create a pull request following the guidelines in the Contributing section below.
Contributions to this repository are welcome! If you'd like to contribute, please follow these guidelines:
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Fork the repository to your GitHub account.
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Create a new branch for your contribution.
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Make your changes (add new questions, improve solutions, etc.).
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Ensure your code is well-documented and follows best practices.
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Test your changes to ensure they work correctly.
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Commit your changes with descriptive commit messages.
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Push your changes to your forked repository.
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Create a pull request to the main repository.
Please adhere to the Code of Conduct when contributing to this project.
This project follows an Open Source Code of Conduct. By participating, you are expected to uphold this code of conduct. Please report any unacceptable behavior to [maintainer's email].
This project is licensed under the MIT License. You are free to use, modify, and distribute the code and content within this repository, but please attribute the original work to this repository and consider sharing your contributions back with the community.
Happy interviewing and coding!