Subject: Biostatistics
Course Number: 202
Course Title: Opportunities and challenges of complex biomedical data
Units: 3
School: Graduate Division
Department: Clinical Research Program

Course Description: This is an introduction to the opportunities and challenges of using large datasets for biomedical research. Topics to be covered include: What makes big data different? What big data can and cannot do. Phases of data science: getting data, merging and cleaning data, storing and accessing data, visualizing or telling stories with data, drawing conclusions from data. Introduction to supervised and unsupervised machine learning including detailed discussion of algorithms and model fitting.
Prerequisites: None
Restrictions: This course is part of the Training in Clinical Research (TICR) Program and may have space limitations. Auditing is not permitted.
Activities: Direct - Lecture, Direct - Lab-Skills, Direct - Project, Student - Lecture, Student - Lab-Skills

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

Quarter(s) Offered: Summer
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? No
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