STATS 201: Machine Learning for Social Science
Undergraduate class, Duke Kunshan University, 2026
Class description:
In almost every field, there is a need to draw inferences from or make data-based decisions. This course aims to provide an introduction to machine learning that is approachable to diverse disciplines, empowering students to become proficient in the foundational concepts and tools while working with interdisciplinary, real-world data at the intersection of machine learning and social science. You will learn to:
- Structure a machine learning problem,
- Determine which algorithmic tools apply to a given problem,
- Apply those tools to diverse, interdisciplinary data,
- Evaluate the performance of your solution, and
- Interpret and communicate your results accurately.
This applied introduction to machine learning will arm you with the essential skills to conduct analyses and communicate results effectively. We will cover machine learning methods for text, image, audio, and time series data.