Courses in Data Science

DataLab faculty teach courses in data science for students at all levels. These courses area great way for students interested in the field to gain the training and skills necessary to engage in research at the lab. We also organize the popular Data Science Seminar at the University of Washington,  which features cutting-edge research in data science from prominent scholars in the field.

Data Science for Informatics (Undergraduate)

Courses in data science at the undergraduate level are designed to provide students with the theoretical and practical foundations of data science. The primary focus of this course is on modern statistical and computational tools for analyzing large-scale data, including machine learning and basic econometrics.

MSIM Specialization in Data Science and Analytics

The MSIM specialization in Data Science and Analytics provides students with a practical and theoretical understanding of the key methods and technologies used to analyze and derive insight from large-scale, heterogeneous data. The specialization involves a three quarter core methods sequence: Data Science I: Theoretical Foundations, Data Science II: Machine Learning and Econometrics, and Data Science III: Scaling, Applications and Ethics. These core classes are designed to be taken in sequence. Students must have prior experience with statistics and programming before entering the sequence. We also offer an Introduction to Data Science course for students who do no meet the required prerequisites, or who would like an overview of the field.

Students in the specialization will have the opportunity for further study in a series of additional advanced topics through the concentration electives. Possible electives include:

Ph.D Program in Big Data and Data Science at UW

The path to deep scientific discoveries is changing rapidly. Most disciplines, from physical to life sciences, have entered an era, where discovery is now no longer limited by the collection and processing of data, but by the management, analysis, and visualization of this information. From studying the building blocks of life, to understanding the nature of our universe, transformative breakthroughs are increasingly dependent on our ability to interrogate complex data streams from instruments distributed on a global scale. Similarly, the next generation of computer scientists and statisticians needs to understand deeply the real needs of domain scientists. Students can no longer develop tools and models in isolation, because the resulting “hammers” fail to meet the growing needs of the data-enabled sciences. To address these challenges and to educate the next generation of scientists, the University of Washington offers PhD programs specialized in Big Data and Data Science in various departments as well as an integrative program that crosses department boundaries.