Learning Goals

1. Demonstrate fluency in programming, data analysis, and statistical modeling for applications across diverse domains.
2. Apply conceptual and technical knowledge of core data science methods, including statistical inference, algorithmic problem solving, machine learning, and model evaluation.
3. Integrate interdisciplinary tools and perspectives to formulate, analyze, and solve complex problems using data.
4. Communicate data-driven insights effectively to both technical and non-technical audiences, and critically evaluate the ethical, societal, and policy implications of data science practices.
5. Collaborate on project-based work that integrates computational and mathematical approaches in a capstone experience, demonstrating effective teamwork, professional responsibility, and the ability to integrate diverse methods to solve data-driven problems.