CMPSC 301: Data Science - Fall 2026

Allegheny College | Department of Computer Science

A comprehensive, interactive course website for Data Science (CMPSC 301) featuring JupyterLite integration, interactive Python/R demonstrations, and a colorful, student-friendly design.

🌟 Features

• 🎨 Colorful Design: Vibrant UI inspired by the course logo (cyan, coral, deep blue)
• 🚀 JupyterLite Integration: Full Python environment running in the browser
• 🎮 Interactive Playground: 5 comprehensive data science demonstrations:
  • Data Visualization Masterclass
  • Machine Learning: Predicting the Future
  • Text Analytics & Sentiment Analysis
  • Statistical Analysis: Finding Patterns
  • Data Wrangling: Cleaning Messy Data
• 📚 Course Materials: Weekly schedule with slides, assignments, and resources
• 📥 Project Files Hub: Downloadable datasets, starter code, and tutorials
• 📱 Responsive Design: Works beautifully on desktop, tablet, and mobile

🚀 Quick Start

Option 1: View the Live Site

Visit the deployed site at: https://YOUR-USERNAME.github.io/YOUR-REPO/

Option 2: Build Locally

1. Clone the repository:

   git clone https://github.com/YOUR-USERNAME/YOUR-REPO.git
   cd YOUR-REPO

2. Install Quarto:

   • Download from quarto.org
   • Follow installation instructions for your OS

3. Install Python dependencies (for JupyterLite):

   pip install -r live/requirements.txt

   The pins in that file must stay together — see JUPYTERLITE_SETUP.md §3.

4. Render the site:

   quarto render

5. Build JupyterLite:

   cd live
   jupyter lite build --output-dir ../docs/live

6. Preview locally:

   quarto preview

   or open docs/index.html in your browser

📁 Project Structure

.
├── _quarto.yml              # Main Quarto configuration
├── styles.css               # Custom CSS (logo-inspired colors)
├── logo.png                 # Course logo
├── index.qmd                # Home page (syllabus)
├── README.md                # This file
│
├── playground/              # Interactive demonstrations
│   ├── 00_playground.qmd    # Playground landing page
│   ├── 01_visualization.qmd
│   ├── 02_machine_learning.qmd
│   ├── 03_text_analysis.qmd
│   ├── 04_statistical_analysis.qmd
│   └── 05_data_wrangling.qmd
│
├── materials/               # Course materials
│   ├── 0_materials.qmd      # Weekly schedule
│   ├── 1_project_files.qmd  # Downloads hub
│   └── files/               # Datasets and resources
│
├── live/                    # JupyterLite setup
│   ├── jupyter-lite.json
│   ├── jupyter_lite_config.json
│   ├── content/
│   │   └── welcome.ipynb    # Welcome notebook
│   └── README.md
│
├── docs/                    # Built site (output)
│   ├── index.html
│   ├── live/                # JupyterLite deployment
│   └── ...
│
└── .github/
    └── workflows/
        └── deploy.yml       # GitHub Actions for deployment

🎨 Color Scheme

The site uses colors extracted from the course logo:

• Bright Cyan: #40C9D9 - Primary navigation and accents
• Deep Blue: #2563C7 - Headings and text
• Coral Pink: #FF6B6B - Highlights and calls-to-action
• Turquoise: #4DD4E5 - Secondary accents
• Salmon Coral: #FF7B7C - Interactive elements

🛠️ Customization

Changing Colors

Edit styles.css and update the CSS variables in :root:

:root {
  --bright-cyan: #40C9D9;
  --deep-blue: #2563C7;
  --coral-pink: #FF6B6B;
  /* ... */
}

Adding Pages

1. Create a new .qmd file
2. Add it to _quarto.yml navigation:

   navbar:
     left:
       - href: your-page.qmd
         text: Your Page

Adding Playground Demonstrations

1. Create a new .qmd file in playground/
2. Add frontmatter with title, description, and categories
3. It will automatically appear in the playground listing

Modifying JupyterLite Packages

Packages are installed by students at runtime, in the browser — there is no build-time package list. In a Python notebook:

import micropip
await micropip.install("your-package-here")

In an R notebook:

install.packages("your-package-here")

See live/README.md for details.

🚀 Deployment to GitHub Pages

Automatic Deployment (Recommended)

The repository includes a GitHub Actions workflow that automatically builds and deploys the site when you push to the main branch.

Setup steps:

1. Go to your repository settings
2. Navigate to Pages section
3. Under Source, select GitHub Actions
4. Push to main branch - the site will build automatically!

Manual Deployment

If you prefer manual deployment:

1. Build the site locally:

   quarto render
   cd live && jupyter lite build --output-dir ../docs/live

2. Commit and push the docs/ folder:

   git add docs/
   git commit -m "Deploy site"
   git push

3. Configure GitHub Pages to use the docs/ folder

📚 Course Content

Playground Demonstrations

1. Data Visualization: Creating beautiful charts with Matplotlib, Seaborn, and Plotly
2. Machine Learning: Building predictive models for house prices
3. Text Analytics: Sentiment analysis of product reviews
4. Statistical Analysis: Hypothesis testing and confidence intervals with student data
5. Data Wrangling: Cleaning and transforming messy real-world data

Materials

• Weekly schedule with topics, slides, and assignments
• Downloadable resources: Datasets, starter code, tutorials
• Project guidelines: Midterm and final project requirements

🤝 Contributing

This is a course website template. To adapt it for your course:

1. Fork the repository
2. Update course information in index.qmd
3. Customize colors in styles.css
4. Add your own materials to materials/
5. Modify or add playground demonstrations
6. Update README.md and remove example content

📄 License

This course website is open source. Feel free to use and adapt it for your own courses!

🆘 Support

• Technical Issues: Open an issue on GitHub
• Course Questions: Contact the instructor via email or Discord
• JupyterLite Problems: See live/README.md, or JUPYTERLITE_SETUP.md for the full build/troubleshooting guide

✨ Credits

• Quarto: quarto.org
• JupyterLite: jupyterlite.readthedocs.io
• Design Inspiration: Course logo colors and modern web design principles
• Data Science Libraries: NumPy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-learn

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Built with ❤️ for Data Science Education

Last updated: August 2026