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https://github.com/keneandita/r2ds

A curated, structured learning path covering key concepts, tools, and projects on the journey to becoming a data scientist from Python basics to advanced machine learning.
https://github.com/keneandita/r2ds

data-science jupyter-notebooks portfolio python statistics

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A curated, structured learning path covering key concepts, tools, and projects on the journey to becoming a data scientist from Python basics to advanced machine learning.

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# 📘 `R2DS` - *Road to Data Science*

**R2DS** is my curated, structured learning journey toward becoming a **data scientist**, documenting everything from foundational skills to hands-on projects.

This repo includes notes, notebooks, and learning resources covering Python, statistics, machine learning, and practical data science workflows.

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## Why This Repo?

With the explosion of online courses and tutorials, it's easy to get lost.
This repo keeps me grounded with:

- A clear roadmap from beginner to intermediate data science
- Organized and annotated Jupyter notebooks
- Mini-projects that reinforce key concepts
- A personal record of what I’ve learned and applied

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## Topics Covered

- ✅ Python for Data Science
- ✅ NumPy, Pandas, and data wrangling
- ✅ Exploratory Data Analysis (EDA)
- ✅ Data Visualization (Matplotlib, Seaborn)
- ✅ Statistics & Probability
- ✅ Machine Learning (Scikit-learn)
- ✅ SQL & Databases (in progress)
- ✅ Capstone Projects

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## Learning Sources

I reference a mix of books, courses, and real datasets, including:

- IBM Data Science Professional Certificate
- Kaggle Learn
- StatQuest by Josh Starmer
- *Hands-On ML with Scikit-Learn, Keras & TensorFlow*

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## Contributions

This is a personal learning repo, but I'm happy to collaborate or exchange notes.
Open an issue or reach me at `Keneansufa@gmail.com`.