MACH LEARN FOR SOCIAL SCIENCE

Catalog description

In almost every field, there is a need to draw inference from or make decisions based on data. The goal of this course is to provide an introduction to machine learning that is approachable to diverse disciplines and empowers students to become proficient in the foundational concepts and tools while working with interdisciplinary real-world data. You will learn to (a) structure a machine learning problem, (b) determine which algorithmic tools are applicable to a given problem, (c) apply those algorithmic tools to diverse, interdisciplinary data examples, (d) evaluate the performance of your solution, and (e) how to accurately interpret and communicate your results. This course is a fast-paced, applied introduction to machine learning that arms you with the basic skills you will need in practice to both conduct analyses and effectively communicate your results. 001810