Study Guide 2015-2016

SGN-53007 Computational Diagnostics, 5 cr

Lessons

Study type P1 P2 P3 P4 Summer Lecture times and places
Lectures
Excercises
 4 h/week
 2 h/week


 


 


 


 
Monday 12 - 14 , TB222
Friday 14 - 16 , TC219


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

Target groups:

DI- ja arkkitehtiopiskelijat
International Students
Jatkotutkinto-opiskelijat

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.