Course Catalog » Data Science 225

Subject: Data Science
Course Number: 225
Course Title: Advanced Machine Learning for the Biomedical Sciences II
Units: 3
School: Graduate Division
Department: Clinical Research Program

Course Description: This course covers the underlying formulation of machine learning algorithms. Its focus is on providing deep understanding of machine learning methodology. This is an advanced course in machine learning and its objective is to provide students with a strong foundation so that they can properly manipulate and customize black box machine learning library packages. Students will implement popular machine learning algorithms and customize them to best satisfy specific needs in medicine.
Prerequisites: Biostats 213 or equivalent. Biostat 216 and Biostat 208 or equivalent
Restrictions: This course is part of the Training in Clinical Research (TICR) Program and may have space limitations. Auditing is not permited.
Activities: Direct - Lecture, Direct - Project, Student - Lecture, Student - Project, Student - Independent Study

Instructor of Record: G. Valdes
May the student choose the instructor for this course? No
Does enrollment in this course require instructor approval? No

Quarter(s) Offered: Spring
Course Grading Convention: Letter Grade, P/NP (Pass/Not Pass) or S/U (Satisfactory/Unsatisfactory)
Graduate Division course: Yes
Is this a web-based online course? Yes
Is this an Interprofessional Education (IPE) course? No
May students in the Graduate Division (i.e. pursuing Master or PhD) enroll in this course? Yes
Repeat course for credit? No