Introduction

Data Science Pages is a student-led project designed to teach and promote data science concepts. Inspired by Mr. Mortensen's curriculum, this repository serves as both a learning tool and a collaborative teaching platform. It offers educational content such as tutorials, blogs, coding notebooks, and an interactive single-page resource to guide students through key data science principles.

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Purpose

This project has three main goals:

• Teach Data Science: Offer lessons on topics like statistics, machine learning, data visualization, and Python.
• Promote Peer Learning: Allow students to create and share educational content.
• Provide a Central Hub: Host a single-page website with curated explanations and resources covering major topics in data science.
• Allow Coders to Use and Create: Allow students to create and develop using our ML and functional features for data science

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Key Features

• Single Page Learning Hub
  A centralized page with summaries and visualizations of major data science concepts: variables, functions, algorithms, data analysis, and more.

• Interactive Coding Notebooks
  Jupyter Notebooks with hands-on code and walkthroughs for topics like:

  • Pandas & NumPy
  • Matplotlib & Seaborn
  • Titanic Dataset Explorations
  • Linear Regression and Classification

• Tutorials and Blogs
  Student-authored tutorials, walkthroughs, and reflections on learning and teaching data science.

• Live Demos
  Flask and Python APIs (e.g., Titanic API) that let students analyze and transform real-world data.

• Other Features Include Survivng Sickness, Titanic, AI Trainer, Travel Recommendor, Score Predictor, College Predictor.

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Getting Started

This project has various blogs for every features that has detailed documentations of how to write and understand the code. Refer to those blogs (linked in our head navigatin page) to gain access to the information.

To get started with the project:

1. Clone the Repository

   git clone https://github.com/<your-username>/data-science-pages.git
   cd data-science-pages
   

2. Run Setup Script

For Ubuntu

./scripts/activate_ubuntu.sh

For macOS

./scripts/activate_macos.sh

For Kasm

./scripts/activate_kasm.sh

For WSL (Windows Subsystem for Linux)

./scripts/activate_wsl.sh

3. Install Dependencies

bundle install

4. Start The Server

make

5. Open in Browser

Contribution Ideas

• Write a new tutorial or blog post
• Create or improve a Jupyter Notebook
• Expand the learning hub with new topics
• Build an API or live demo
• Help clean up or review someone else’s code

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License

This project is licensed under the Apache 2.0 License.

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Credits

Developed by students and supported by Mr. Mortensen, this project reflects a community-driven approach to learning and teaching data science.