This repository contains project files and analytical work completed as part of the Google Data Analytics Professional Certificate. The projects are developed and presented using Jupyter Notebook, running locally in a macOS environment, with the source files made available through GitHub. The analyses demonstrate practical applications of data analytics techniques, including data preparation, cleaning, exploration, visualization, and interpretation. The projects are built primarily with Python and utilize widely adopted data science and analytics libraries, including NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn. Together, these projects provide examples of working with real-world datasets and applying Python-based analytical workflows to transform raw data into meaningful insights. The notebooks document the analytical process and provide a reproducible view of the methods, calculations, visualizations, and findings developed throughout the certificate program.