Applied Data Analysis (ADAT)

Programming for Data Analysis is a hands-on, applied course designed to give you the programming skills needed to unlock the power of data. Whether you’re cleaning messy datasets, automating analysis, or building data pipelines, you’ll learn how to write code that makes data work for you. This course may not be repeated for degree credit.

This course may not be repeated for degree credit.

This course may not be repeated for degree credit.

This course covers questions about 1) Data confidentiality and privacy, 2) Data management, organization, and documentation, 3) Data accountability and transparency, 4) Presentation and communication of data and analysis, and 5) Data ethics. This course may not be repeated for degree credit.

Data Visualization brings data to life through compelling and informative visual storytelling. In this course, you’ll learn to design and build effective and interactive visualizations that help uncover patterns, communicate insights, and support decision-making in politics, business, and society. This course may not be repeated for degree credit.

In this one, two, three, or four unit course, the student will have the opportunity to work closely with a professor on a quantitative research project in the social sciences or humanities, either independently or collaboratively. In this capacity, the student will receive training in data collection, how to analyze and interpret the results from data. The student will also be assessed at various stages of the course using suitable techniques such as weekly meetings, assignments, and a written report.

Studies pursue an independent research project utilizing advanced quantitative methods under the supervision of faculty.