https://github.com/AsuquoAA/Applied_Data_Science_with_Python_Study
https://github.com/AsuquoAA/Applied_Data_Science_with_Python_Study
matplotlib numpy pandas seaborn
Last synced: 7 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/AsuquoAA/Applied_Data_Science_with_Python_Study
- Owner: Lazycodes
- Created: 2024-11-16T19:31:41.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-21T13:06:28.000Z (about 1 year ago)
- Last Synced: 2024-11-21T14:19:34.126Z (about 1 year ago)
- Topics: matplotlib, numpy, pandas, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 30.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Applied Data Science with Python Specialization
## Overview
This repository contains my study from the **Applied Data Science with Python Specialization** by the University of Michigan. The specialization focuses on applying data science techniques using Python, including tools and libraries such as Pandas, Matplotlib, Seaborn, Scikit and others.
---
## About
The **Applied Data Science with Python Specialization** is a comprehensive 5-course series that teaches practical skills for data science using Python. It covers topics ranging from data analysis, visualization, and machine learning to text mining and applied data science.
The courses in this specialization emphasize learning by doing and apply concepts in real-world situations.
---
## Courses in the Specialization
This specialization consists of the following courses:
1. **Introduction to Data Science in Python**
- Focus on using NumPy and Pandas for Data Preparation
2. **Applied Plotting, Charting, and Data Representation with Python**
- Focus on using Matplotlib and Seaborn for data visualization.
3. **Applied Machine Learning in Python**
- Introduction to machine learning techniques using Scikit-learn.
4. **Applied Text Mining with Python**
- Explore text mining techniques using Python libraries such as NLTK and Scikit-learn.
5. **Applied Social Network Analysis with Python**
- Learn the basics of network analysis using NetworkX.
---
## Skills Acquired
I developed skills in:
- **Data Visualization**: Using Matplotlib and Seaborn to create informative and appealing visualizations.
- **Data Wrangling**: Preprocessing, cleaning, and manipulating data using Pandas.
---
## Dependencies
To use this repository and run the notebooks, you will need to have Python and the following libraries installed:
1. Pandas
2. NumPy
3. Matplotlib
4. Seaborn
- code: pip install numpy pandas matplotlib seaborn jupyter
## Installation
To get started with this repository, clone it to your local machine:
- code: git clone https://github.com/Lazycodes/Applied_Data_Science_with_Python_Study.git
Navigating to directory
- code: cd Applied_Data_Science_with_Python_Study
---
## License
This repository is for educational purposes only. It is not affiliated with the University of Michigan or Coursera.
## Acknowledgements
I would like to thank the University of Michigan and Coursera for providing the Applied Data Science with Python Specialization, which has been an invaluable resource for learning data science with Python. The course materials have greatly contributed to my understanding of the practical applications of data science techniques and tools. This repository contains solutions, projects, and assignments created as part of the coursework, and all content is for educational purposes only.