Dive into a comprehensive 46-minute tutorial on getting started with data science, covering essential topics from project structure to advanced GitHub integration. Learn to create and manage GitHub repositories, utilize GitHub Codespaces, and leverage Google Colab for collaborative data analysis. Master data ingestion techniques, explore descriptive statistics with Pandas, and create insightful visualizations using Seaborn. Discover how to merge datasets, export results, and implement continuous integration for Jupyter notebooks using GitHub Actions. Gain practical skills in creating Makefiles, testing notebooks with nbval plugin, and utilizing GitHub status badges to showcase your project's integrity.