Applied data science is already shaping how the world tackles pressing social challenges — from fighting discrimination, to allocating resources for refugees, to managing water scarcity. This course invites students from a wide range of backgrounds — social sciences, policy, business, environmental studies, or anyone simply curious about data — to learn how to use data science tools in ways that matter.
Over fifteen weeks, you'll get hands-on experience with Python in Google Colab (no installation required), organize your work on GitHub, create interactive visualizations with Plotly, and even try your hand at building a simple application in Streamlit. You'll also see how modern AI coding assistants can serve as partners in debugging, exploration, and idea generation.
Materials for each week can be found in the ./week* folders. See README.md for further details and instructions.
Any technical issues, ideas, bugs in course materials, contribution ideas - add an issue.
By the end of the course, you will be able to:
✅ Collect and prepare real-world datasets for analysis
✅ Visualize complex information with clear, interactive charts
✅ Build a basic predictive model and interpret its results in plain language
✅ Share your work through well-structured GitHub repositories
✅ Create and publish a lightweight data app to communicate your findings
Format: 1 class per week (180 min)
Each of the first 13 sessions: ~90 min lecture + ~90 min tutorial. Homework is optional except for a mid-term assignments and a capstone project.
Week 14: Open office hours for project help
Week 15: Capstone showcase
Throughout the course, you'll work toward a final individual project where you choose a social issue that matters to you and use data to explore, explain, or propose solutions.
Your capstone will include:
• Data collection from real-world sources relevant to your chosen issue
• Interactive visualizations that tell a compelling story
• Predictive analysis with clear, accessible interpretations
• A deployed Streamlit app that communicates your findings
• Professional GitHub repository documenting your work
Example project domains:
- Educational equity and resource allocation
- Climate change impact analysis
- Public health and healthcare access
- Economic inequality and policy impact
- Social justice and discrimination patterns
- Global development and humanitarian aid
- Freedom of speech and censorship
This hands-on approach ensures you gain practical experience while making a meaningful contribution to causes you care about.
This course can be completed in self-paced mode but currently runs as 1-semester course through Smolny Beyond Borders initiative at Bard College.
This course is created by a team of data science practitioners and researchers dedicated to making data science education accessible and practical:
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Course Lead: Anastasiia Kulakova
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Educational Institution Partner: Smolny Beyond Borders: A Liberal Arts Initiative
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Non-profit Partner: Russian Independent Media Archive
- No prior coding experience required!
- Curiosity about social issues and data
- Access to a web browser and internet connection
- Google Colab: Python programming environment (no installation needed)
- Databricks: Data environment (no installation needed)
- GitHub: Project organization and version control
- Plotly: Interactive data visualization
- Streamlit: Building and deploying simple web applications
- AI Coding Assistants: ChatGPT, GitHub Copilot for learning support
pandas: Data manipulation and analysisplotly: Interactive visualizationsstreamlit: Web app developmentrequests: API data collectionscikit-learn: Basic machine learning
All alternatives provided when needed — you can fully participate from anywhere in the world!
We welcome contributions! Please see our Contributing Guidelines for details on how to contribute to this course.
This project is licensed under the MIT License - see the LICENSE file for details.
Special thanks to all the organizations and individuals working at the intersection of data science and social impact, and to our students who inspire us with their passion for positive change.
Ready to use data science for social good? Begin with Week 1 and let's start making a difference together! 🌍