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*Road to Data Science*\n\n**R2DS** is my curated, structured learning journey toward becoming a **data scientist**, documenting everything from foundational skills to hands-on projects.\n\nThis repo includes notes, notebooks, and learning resources covering Python, statistics, machine learning, and practical data science workflows.\n\n---\n\n## Why This Repo?\n\nWith the explosion of online courses and tutorials, it's easy to get lost.  \nThis repo keeps me grounded with:\n\n- A clear roadmap from beginner to intermediate data science\n- Organized and annotated Jupyter notebooks\n- Mini-projects that reinforce key concepts\n- A personal record of what I’ve learned and applied\n\n---\n\n## Topics Covered\n\n- ✅ Python for Data Science\n- ✅ NumPy, Pandas, and data wrangling\n- ✅ Exploratory Data Analysis (EDA)\n- ✅ Data Visualization (Matplotlib, Seaborn)\n- ✅ Statistics \u0026 Probability\n- ✅ Machine Learning (Scikit-learn)\n- ✅ SQL \u0026 Databases (in progress)\n- ✅ Capstone Projects\n\n---\n\n## Learning Sources\n\nI reference a mix of books, courses, and real datasets, including:\n\n- IBM Data Science Professional Certificate\n- Kaggle Learn\n- StatQuest by Josh Starmer\n- *Hands-On ML with Scikit-Learn, Keras \u0026 TensorFlow*\n\n---\n\n## Contributions\n\nThis is a personal learning repo, but I'm happy to collaborate or exchange notes.\nOpen an issue or reach me at `Keneansufa@gmail.com`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeneandita%2Fr2ds","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkeneandita%2Fr2ds","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeneandita%2Fr2ds/lists"}