Beginner-Data-Science-Projects

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This repository is a curated collection of hands-on data science projects tailored for beginners. Whether you're just starting your journey in data science or looking to strengthen your skills, these projects provide a practical and interactive way to apply your knowledge.

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- - bug_report.md
  - new_project.md
- pull_request_template.md
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - KDDCup Data 10 Percent.csv
  - kddcup.txt
  - NIDS.ipynb
  - README.md
  - requirements.txt
  - training_attack_types.txt
  - Workshop Dataset.csv
- README.md
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - customer_churn.csv
  - customerChurn.ipynb
  - new_customers_1.csv
  - README.md
  - requirements.txt
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - heart_failure.ipynb
  - heart_failure_clinical_records_dataset.csv.xls
  - README.md
  - requirements.txt
- - Iris_Flower.ipynb
  - README.md
  - requirements.txt
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- README.md
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_data_cleaning.ipynb
  - 03_model_building.ipynb
  - README.md
  - requirements.txt
  - utils.py
- README.md
- - Alzheimer.ipynb
  - CSI_7_MAL_2324_CW_resit_data.xlsx
  - README.md
  - requirements.txt
- - 01_eda.ipynb
  - 02_model_building.ipynb
  - make_data.py
  - README.md
  - requirements.txt
  - utils.py
- - 01_dominant_colors.ipynb
  - 02_named_colors.ipynb
  - make_data.py
  - README.md
  - requirements.txt
  - utils.py
- - 01_edge_and_contour.ipynb
  - 02_perspective_and_scan.ipynb
  - make_data.py
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_model_building.ipynb
  - make_data.py
  - README.md
  - requirements.txt
  - utils.py
- - 01_eda.ipynb
  - 02_model_building.ipynb
  - make_data.py
  - README.md
  - requirements.txt
  - utils.py
- - augment_images.ipynb
  - model.ipynb
  - README.md
  - requirements.txt
.gitignore
CONTRIBUTING.md

# Installation Guide

1. Get the code

git clone https://github.com/tkarim45/Beginner-Data-Science-Projects

Downloads the entire project code from GitHub to your computer.

cd Beginner-Data-Science-Projects

Moves into the project folder you just downloaded.

2. Official Install Script

Easy Recommended

Prerequisites

Python 3 Python is required to use pip.

pip install pandas numpy matplotlib seaborn scikit-learn jupyter

Installs the package published on PyPI directly — no need to clone the source.

✅ After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.

Pulled directly from this repo's README.

3. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install pandas numpy matplotlib seaborn scikit-learn jupyter

Installs the package published on PyPI directly — no need to clone the source.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

jupyter notebook

Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.

✅ If it runs without errors and prints output in the terminal, it worked.

Pulled directly from this repo's README.

// repository documentation

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