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Learn Python for Data - From Scratch to Advanced

Welcome to the "Learn Python for Data" repository! Whether you're a seasoned engineer looking to expand your skill set or someone who wants to learn Python from scratch specifically for data-related tasks, you're in the right place. This repository aims to cover everything you need to know about Python for handling and analyzing data. Each concept and code will be explained in detail with suitable illustrations to make learning easy and enjoyable.

Hit the Star! ⭐

If you're planning on using this Python repository for learning, please consider giving it a star⭐
Thank you!

For Doubts and Queries

Feel free to connect with me on LinkedIn through this profile: https://www.linkedin.com/in/sahdevgrover/

About the Instructor

Instructor: Sumit Mittal

Sumit Mittal is an experienced engineer and a Big Data expert with a passion for teaching. With years of industry experience, Sumit brings practical knowledge and expertise to his tutorials, making complex concepts accessible to learners of all levels.

Python Playlist

For video tutorials accompanying this repository, please check out the Python playlist on YouTube:

Python Playlist

Contents

This repository will cover a wide range of topics related to Python for data, including but not limited to:

  • Python basics
  • Data types and data structures
  • Control flow (loops, conditionals)
  • Functions and modules
  • File handling
  • Object-oriented programming (OOP)
  • Working with libraries such as NumPy, Pandas, Matplotlib, and more
  • Data manipulation and analysis
  • Data visualization
  • Advanced topics (machine learning, web scraping, etc.)

How to Use This Repository

  1. Clone the Repository: Start by cloning this repository to your local machine using the following command:

  2. Navigate Through Content: Explore the repository to find tutorials, code samples, and additional resources organized by topics.

  3. Watch the Videos: Refer to the provided YouTube playlist for video tutorials corresponding to the topics covered in this repository.

  4. Learn and Practice: Follow along with the tutorials, run the code samples, and experiment with the concepts on your own machine. Learning by doing is key!

Contribution

Contributions to this repository are welcome! If you have suggestions for improvements, additional topics to cover, or find any errors, please feel free to open an issue or submit a pull request.

Let's learn Python for data together and embark on an exciting journey into the world of data science and analytics!

Happy coding!

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