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Data Science Bootcamp

Welcome to the Data Science Bootcamp repository! 🎉 This repository contains projects and code notebooks I created while following a comprehensive Udemy course on Python for Data Science and Machine Learning Bootcamp by Jose Portilla and Pierian Training.

🚀 About This Repository

This repository showcases my learning journey in Data Science. The projects and code here are based on the topics covered in the course, reflecting the skills I have developed in:

  • Data Analysis and Visualization
  • Python Programming

It serves as a portfolio of my hands-on experience and understanding of essential Data Science concepts.

📚 Topics Covered

Programming with Python

  • Essential Python programming concepts.

Data Analysis and Manipulation

  • NumPy: High-performance numerical computations.
  • pandas: Working with DataFrames to tackle complex data tasks.
  • Handling Excel files with pandas.

Data Visualization

  • matplotlib and seaborn: Create static, beautiful visualizations.
  • plotly: Build interactive visualizations.

...and much more!

🗂️ Repository Structure

This repository is organized as follows:

📂 data_science_bootcamp
├── 📁 01-Python-Crash-Course
│   ├── 01-Python Crash Course.ipynb
│   ├── 02-Python Crash Course Exercises.ipynb
│   └── 03-Python Crash Course Exercises - Solutions.ipynb
├── 📁 02-Python-for-Data-Analysis-NumPy
├── 📁 03-Python-for-Data-Analysis-Pandas
├── 📁 04-Pandas-Exercises
├── 📁 05-Data-Visualization-with-Matplotlib
├── 📁 06-Data-Visualization-with-Seaborn
├── 📁 07-Pandas-Built-in-Data-Viz
├── 📁 08-Plotly-and-Cufflinks
├── 📁 09-Geographical-Plotting
├── README.md  # (You're here!)

💻 Getting Started

  1. Clone this repository:

    git clone https://github.com/yourusername/data_science_bootcamp.git
cd data_science_bootcamp

  2. Install required dependencies:

    pip install -r requirements.txt

  3. Explore the notebooks in the folder to follow along with the projects and code.

🎓 Learning Outcomes

By working through this repository, I have gained the ability to:

  • Analyze datasets and derive meaningful insights.
  • Build compelling visualizations to tell data stories.
  • Implement machine learning models to solve various problems.

This repository demonstrates my dedication to learning and applying Data Science skills.

🛠️ Tools and Technologies

  • Python: The core programming language.
  • NumPy, pandas: Data manipulation and analysis.
  • matplotlib, seaborn, plotly: Data visualization.
  • SciKit Learn: Machine learning models.
  • Jupyter Notebook: Interactive coding environment.

🌟 Acknowledgments

This repository contains my personal projects and exercises based on the Udemy course "Python for Data Science and Machine Learning Bootcamp by Jose Portilla and Pierian Training". Thank you to the course creators for providing such valuable learning resources!

📬 Contact

For questions or suggestions, feel free to reach out:

Happy Learning! 🎉