Update README.md

Author: mr-pylin

README.md

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-# numpy-workshop
+# 🔢 NumPy Workshop
 An in-depth guide to mastering NumPy, covering fundamental to advanced array operations for data science and numerical computing.
+
+## 📋 Table of Contents
+0. [Array](./codes/00_array.ipynb)
+ - Introduction to NumPy arrays
+1. [Arithmetic Operations](./codes/01_arithmetic-operations.ipynb)
+ - Arithmetic operations
+ - Operations between (array & scalar) and (array & array)
+2. [Comparative Operations](./codes/02_comparative-operations.ipynb)
+ - Comparative operations
+ - Operations between (array & scalar) and (array & array)
+3. [Index & Slice](./codes/03_index-&-slice.ipynb)
+ - Indexing and slicing arrays
+ - Advanced indexing techniques
+ - Mask & Filters
+ - Integer & Boolean array indexing
+4. [Axes](./codes/04_axes.ipynb)
+ - Understanding axes in NumPy
+5. [Modifications](./codes/05_modifications.ipynb)
+6. [ndarray](./codes/06_ndarray.ipynb)
+7. [Array Creation](./codes/07_array-creation.ipynb)
+8. [Mathematics](./codes/08_mathematics.ipynb)
+9. [Statistics](./codes/09_statistics.ipynb)
+10. [Sort, Search & Count](./codes/10_sort-search-count.ipynb)
+11. [Logic](./codes/11_logic.ipynb)
+12. [Set](./codes/12_set.ipynb)
+13. [Linear Algebra](./codes/13_linear-algebra.ipynb)
+14. [Structured Array](./codes/14_structured-array.ipynb)
+15. [Input/Output](./codes/15_input-output.ipynb)
+16. [Random Generator](./codes/16_random-generator.ipynb)
+17. [Fourier Transform](./codes/17_fourier-transform.ipynb)
+18. [Efficient Computing](./codes/18_efficient-computing.ipynb)
+19. [Miscellaneous](./codes/19_miscellaneous.ipynb)
+20. [Looking Ahead](./codes/20_looking-ahead.ipynb)
+
+## 📦 Installing Dependencies
+You can install all dependencies listed in `requirements.txt` using [pip](https://pip.pypa.io/en/stable/installation/).
+```bash
+pip install -r requirements.txt
+```
+**Note:** This project was developed using Python `v3.12.3`. If you encounter issues running the dependencies or code, consider using this specific Python version.
+
+## 🛠️ Usage
+ - Open the root folder with [VS Code](https://code.visualstudio.com/)
+ - **Windows/Linux**: `Ctrl + K` followed by `Ctrl + O`
+ - **macOS**: `Cmd + K` followed by `Cmd + O`
+ - Open `.ipynb` files using [Jupyter](https://jupyter.org/) extension integrated with VS Code
+ - Allow Visual Studio Code to install any recommended dependencies for working with Jupyter Notebooks.
+ - Jupyter is integrated with both [VS Code](https://code.visualstudio.com/) & [Google Colab](https://colab.research.google.com/)
+
+## 🔍 Find Me
+Any mistakes, suggestions, or contributions? Feel free to reach out to me at:
+ - 📍[linktr.ee/mr_pylin](https://linktr.ee/mr_pylin)
+ 
+I look forward to connecting with you! 
+
+## 🔗 Usefull Links
+ - **NumPy Website**:
+ - The official website for NumPy, providing information, tutorials, and resources for the NumPy library
+ - Link: [numpy.org](https://numpy.org/)
+ - **NumPy Documentation**:
+ - Comprehensive guide and reference for all functionalities and features of the NumPy library
+ - Link: [numpy.org/doc](https://numpy.org/doc/)
+ - **NumPy Source Code**:
+ - Over 1500 contributers are currently working on NumPy.
+ - Link: [github.com/numpy/numpy](https://github.com/numpy/numpy)
+ - **Looking Ahead**:
+ - Pandas
+ - A powerful, open-source data analysis and manipulation library for Python
+ - Pandas is built on top of NumPy
+ - Link: [pandas.pydata.org/](https://pandas.pydata.org/)
+ - MatPlotLib
+ - A comprehensive library for creating static, animated, and interactive visualizations in Python
+ - Link: [matplotlib.org](https://matplotlib.org/)