- Schedule of Classes - January 31, 2019 7:14PM EST
- Course Catalog - January 31, 2019 7:15PM EST
Course information provided by the Courses of Study 2018-2019.
Course provides a theoretical foundation for advanced machine learning methods applicable to the analysis of large-scale biomedical data. These applications often have two distinct goals: (1) computation of predictions, and (2) understanding underlying biological mechanisms. A range of examples will be included that cover various data modalities (e.g., DNA sequence data, electronic health record data, images) and different goals. There will be a class project that will involve identifying a data-set, selection of appropriate machine learning problem, writing code and conducting analyses, an oral presentation of results and a written report.
When Offered Fall.
Prerequisites/Corequisites Prerequisite: Linear Algebra (MATH 2940 or equivalent), and Probabilistic Modeling and/or Statistical Analysis (such as BTRY 3010 or CEE 3040). Recommended: CS 1110 or CS 1112 or equivalent; Permission required if prerequisites not met.
Disabled for this roster.