Code4Cause

Our work

Technology with a real purpose.

We help students learn programming and machine learning by applying their skills to real-world problems in their communities.

Exploring healthcare through AI

Can data help us understand disease risks?

RiskScan · Healthcare & Machine Learning

Summer 2026 · Healthcare AI

RiskScan

Turning health data into meaningful research.

RiskScan introduced students to the applications of machine learning in healthcare. Over five weeks, students learned Python, data analysis, and machine learning to explore cancer risks and disease trends using real-world health datasets. They developed predictive models, analyzed patterns in the data, and wrote research papers presenting their methods, results, and findings.

  • Python
  • Pandas
  • Data analysis
  • Machine learning
  • Healthcare research

What students made

Students developed machine learning models to investigate disease-related patterns and produced research papers documenting their methodology, analysis, and conclusions.

5 weeks from learning Python to conducting research

Student Research Spotlight

Can Machine Learning Identify Cancer

Saanchi Kaasi | RiskScan Summer Program Student?

Saanchi explored how machine learning can identify patterns associated with cancer using patient lifestyle and health data. Using Python, she trained and compared Random Forest and XGBoost models, achieving 77% and 75.75% accuracy, respectively. Her research also examined the influence of factors such as smoking, diet, and age on model predictions, demonstrating how data science can help researchers better understand cancer-related risks.

  • Python
  • Random Forest
  • XGBoost
  • Healthcare AI
  • Data Analysis
RiskScan student research graph showing cancer risk analysis

A question close to home

Where should we plant more trees?

GreenSight · Bay Area

Summer 2025 · Our first program · Bay Area

GreenSight

From zero coding to local research.

GreenSight introduced middle schoolers to data science through a real-world environmental problem. Over four weeks, students with no prior coding experience learned Python, explored data analysis, and used machine learning to investigate where trees should be planted in the Bay Area. Their work developed into a research paper shared as a final result.

  • Python
  • Data analysis
  • Machine learning

What students made

Students created a research paper identifying potential tree-planting locations and shared their findings with local city council members.

5 weeks from first code to research

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Let’s talk about what’s next.

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