IBM Data Science Workspace

Welcome to the IBM Data Science Workspace – a comprehensive collection of Jupyter notebooks, exercises, and projects completed as part of the IBM Data Science Professional Certificate on Coursera.

This repository showcases hands-on work across key data science topics including Python programming, data analysis, data visualization, machine learning, and working with real-world datasets.

📂 Repository Structure

IBM-Data-Science-Workspace/
│
├── 01-tools-for-data-science/
│   └── Tools for Data Science.ipynb
│
├── 02-open-source-tools/
│   └── Open Source Tools for Data Science.ipynb
│
├── 03-data-science-methodology/
│   └── Data Science Methodology.ipynb
│
├── 04-python-for-data-science/
│   ├── Python Basics.ipynb
│   ├── Python Data Structures.ipynb
│   └── Working with Data in Python.ipynb
│
├── 05-databases-sql-python/
│   └── SQL for Data Science.ipynb
│
├── 06-data-analysis-pandas/
│   └── Data Analysis with Pandas.ipynb
│
├── 07-data-visualization/
│   └── Data Visualization with Python.ipynb
│
├── 08-machine-learning/
│   └── Supervised Learning.ipynb
│
├── 09-applied-data-science-capstone/
│   └── Capstone Project.ipynb
│
└── README.md

📘 Courses Covered

This repo includes practical work from the following courses in the IBM Data Science track:

• Tools for Data Science
• Open Source Tools for Data Science
• Data Science Methodology
• Python for Data Science, AI & Development
• Databases and SQL for Data Science
• Data Analysis with Python
• Data Visualization with Python
• Machine Learning with Python
• Applied Data Science Capstone

🛠️ Technologies Used

• Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
• Jupyter Notebooks
• SQL (IBM Db2, SQLAlchemy)
• Watson Studio (IBM Cloud)
• API Integration and Web Scraping
• Folium, BeautifulSoup, and more

🧐 Highlights

• End-to-end machine learning workflow with real-world datasets.
• Exploratory Data Analysis (EDA) and visual storytelling.
• Use of IBM Watson tools for model building and deployment.
• Capstone Project: Applied data science on a location-based dataset.

🚀 Getting Started

1. Clone this repository:

   git clone https://github.com/oluwaseunolusanya/IBM-Data-Science-Workspace.git

2. Open the notebooks in JupyterLab, VSCode, or IBM Watson Studio.

3. Follow each notebook step-by-step.

📄 License

This project is for learning and demonstration purposes. Refer to the Coursera Honor Code for academic integrity.

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👤 Author: Oluwaseun Olusanya 📟 This repository serves as a portfolio of completed coursework and projects from IBM's Data Science Certification program.