BSTA 522 – Statistical Learning and Data Science
Biography
This course is designed to introduce theory and methods for statistical learning and data science. Data science is an emerging field that overlaps with computer science, artificial intelligence, machine learning/deep learning and statistics. This is an exciting time to observe the birth of the new field. In recent years, statistical learning has been increasingly becoming crucial in data science. Ever-increasing data complexity and unconventional data create new challenges for traditional statistical learning, and this is an active research area. This course will cover traditional statistical learning methods as well as newer methods for such challenges.
Prerequisites:
- BSTA 512/612 Linear Models
¹ CEPH Primary Instructional Faculty
² CEPH Non-Primary Instructional Faculty
Experienced Faculty With Diverse Backgrounds
More than 150 faculty members work within the OHSU-PSU School of Public Health. They have a wide range of expertise, from monitoring and assessing health risks and opportunities in populations, to helping build health-supporting social environments through policy, advocacy, and programs. They are educators, advisors, researchers, practitioners and community leaders. They come from backgrounds in quantitative, behavioral, environmental and social sciences, policy and government, exercise and health sciences and anthropology, among many other areas. They all work in collaboration with each other and with community partners, and are especially focused on the training and education of future leaders and practitioners in the public health fields.
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