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A-Z Guide to Python in Data Science πŸ‘‹πŸ›’

Welcome to the A-Z Guide to Python in Data Science repository! This comprehensive supplement offers an exhaustive exploration of Python in the context of Data Science, covering topics from basic to advanced levels of proficiency.

OverviewπŸ‘‹πŸ›’

The A-Z Guide to Python in Data Science is your go-to resource for mastering Python's applications in the field of Data Science. Whether you're a novice looking to build a solid foundation or an experienced practitioner aiming to enhance your skills, this repository caters to learners at all levels.

FeaturesπŸ‘‹πŸ›’

1- Comprehensive Coverage: Delve into the vast landscape of Python in Data Science, encompassing fundamental concepts, libraries, tools, and advanced techniques essential for data analysis, visualization, machine learning, and more.

2-Progressive Learning Path: Follow a structured learning path that starts with foundational Python concepts and gradually progresses to advanced topics, ensuring a smooth and comprehensive learning experience.

3- Practical Implementations: Gain practical insights through hands-on implementation examples, exercises, and projects that reinforce theoretical knowledge and foster a deeper understanding of Python's role in Data Science.

4- Supplementary Resources: Access additional resources, including articles, tutorials, datasets, and recommended readings, to supplement your learning journey and stay updated with the latest developments in Python and Data Science.

ContentsπŸ‘‹πŸ›’

1- Foundations: Explore basic Python syntax, data types, control structures, functions, and object-oriented programming principles.

2-Data Manipulation and Analysis: Learn how to work with data using popular Python libraries such as NumPy, pandas, and matplotlib for tasks like data cleaning, transformation, aggregation, and visualization.

3- Machine Learning with Python: Dive into the world of machine learning using libraries like scikit-learn and TensorFlow/Keras, covering topics such as regression, classification, clustering, and neural networks.

ContributingπŸ™Œ

Contributions are welcome! Whether it's fixing a bug, enhancing existing content, or adding new material, your contributions can help improve the learning experience for others. Please contact me on skype:themushtaq48, email:[email protected] for guidelines on how to contribute.

Also please subscribe to my Youtube channel

πŸ“¬Contact

If you want to contact me, you can reach me through following social handles.

πŸ™ Special thanks πŸ™ to our Virtual University of Pakistan students (Mr Saad Abbasi), reviewers, and content contributors, notably Dr Said Nabi

                              Star this repo if you find it useful ⭐
                              Also please subscribe to my [Youtube channel](https://www.youtube.com/@coursesteach-mv5si)

πŸ“• Getting Started-Course 01 - 🐍Introduction of Python

Tutorial Video▢️ Code
🌐1- Setup Environment for Python⭐️ 1 Content 3
🌐1- What is mean by programming⭐️ 1-2 Content 3
🌐2- What is Python⭐️ 1-2 Content 6
🌐3- Python integrated development environment (IDE) --- ---
🌐4- Best Free Resources to Learn Python --- ---
🌐5- Understanding Variables and Types in Python Content 2 Colab icon
🌐6-Understanding Operators in Python: A Comprehensive Guide 1 Colab icon
🌐7-Understanding string in Python Content 2 Colab icon
🌐8- Understanding Control Flow in Python Content 2 Colab icon
🌐9- Loops and Iterables 1-2 Colab icon
🌐10-Function 1-2 Colab icon
🌐11- Dictionaries Content 2 Colab icon
🌐12- List Content 2 Colab icon
🌐13-Classes and Objects Content 2 Colab icon
🌐14-Modules 1 Colab icon
🌐15-Packages 1 Colab icon
🌐16-File handling -- Colab icon

πŸ“• Course 02 - πŸ› οΈMachine Learning Libraries

πŸ“šChapter: 1 - NumPy

Tutorial Video Code
🌐1- Exploring the Power of Machine Learning Libraries in Python⭐️ Content 2 Colab icon
🌐2- NumPy-Create Array⭐️ 1 Colab icon
🌐3- NumPy-Arithmetic Operation⭐️ -- Colab icon
🌐4- NumPy-Basics operations⭐️ -- Colab icon
🌐5- NumPy for Statistical Analysis⭐️ 1-2-3-4 Colab icon
🌐5- NumPy for Linear Algebra -- Colab icon
🌐6- NumPy for Data Cleaning -- Colab icon

πŸ“šChapter: 2 - Pandas

Tutorial Video Code
🌐1- Introduction of Pandas 1-2 Colab icon
🌐2-Pandas Data Structures 1-2 Colab icon
🌐3-Data Preparation using pandas 1-2 Colab icon
🌐4-Data Visualization with Pandas 1 Colab icon
🌐5-Data Visualization with Pandas -- Colab icon

πŸ“šChapter: 3 - Exploratory Data Analysis(EDA)

Tutorial Video Code
🌐1-Skimpy 1 Colab icon
🌐2-Sweetviz 1 Colab icon
🌐3-Cufflinks --- Colab icon
🌐5-Pandas Profiling --- Colab icon
🌐6-Chartify --- Colab icon
🌐7-pygwalker 1 Colab icon
🌐8-Vizard --- Colab icon
🌐9-Matplotlib --- Colab icon
🌐10-seaborn --- Colab icon
🌐11-plotly.express --- Colab icon
🌐12-ydata-profiling --- Colab icon
🌐13-Vega-Altair --- Colab icon

πŸ“• Resources - Other Best Free Resources to Learn Python

Module 01: Basics

================================================================

  1. Basic
  2. Projects

Module 02: Projects that needs to be solved

================================================================

  1. Python Projects need to be solve.

Module 03: Important Python Language Resources

================================================================

  1. Impotant Python resourses

πŸ’» Workflow:

  • Fork the repository

  • Clone your forked repository using terminal or gitbash.

  • Make changes to the cloned repository

  • Add, Commit and Push

  • Then in Github, in your cloned repository find the option to make a pull request

print("Start contributing for Python")

πŸ”Explore moreπŸ‘‹πŸ›’

Explore cutting-edge tools and Python libraries, access insightful slides and source code, and tap into a wealth of free online courses from top universities and organizations. Connect with like-minded individuals on Reddit, Facebook, and beyond, and stay updated with our YouTube channel and GitHub repository. Don’t wait β€” enroll now and unleash your.

✨Top Contributors

We would love your help in making this repository even better! If you know of an amazing Python course that isn't listed here, or if you have any suggestions for improvement in any course content, feel free to open an issue or submit a course contribution request.

                   Together, let's make this the best AI learning hub website! πŸš€

Thanks goes to these Wonderful People. Contributions of any kind are welcome!πŸš€

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This repository is related to all about Python - an A-Z guide to the world of Data Science. This supplement contains the implementation of Python from Basic to advance level. Follow Coursesteach for more content 😊

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