Solving Real Problems with Data Science

Catalog description

The hardest part of most data science classes is often model fitting, but the hardest part of being an effective data science professional is understanding your stakeholder's problem, fitting the right model for the problem being solved, and communicating findings. This class fills the gap between neatly curated classroom exercises and the messiness of the real world. It provides a unified perspective on how the material learned in other courses complements one another, and when different approaches to data science are most appropriate to use. It provides a framework for understanding your goals as a data scientist, and how to achieve them. Assumes familiarity with introductory statistical inference and machine learning, covers but does not assume familiarity with causal inference.