SGN-53007 Computational Diagnostics, 5 cr
Lessons
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Description:
After completing the course, the student gained a basic understanding of the definition and the meaning of computational diagnostics and its utility for biomedical research. Case studies will be discussed illustrating the interplay between computational and statistical methods that are applied to large-scale and high-dimensional data sets from genomic and genetic experiments. Moreover, the student will learn how to practically approach such problems by using the statistical programming language R. In general, the course teaches statistical thinking in the context of biomedical problems, i.e., the adaptation of machine learning methods in a problem specific manner.
Person responsible:
Frank Emmert-Streib
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Additional information of course implementation:
See http://www.bio-complexity.com under the Teaching section.