SGN-54106 Computational Diagnostics, 5 cr

Toteutuskerta SGN-54106 2019-01

Kuvaus

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.

Opetus

Periodi 4
Opetusmuodot Tentti
Vastuuhenkilö Frank Emmert-Streib

Arvosteluasteikko

Numerical evaluation scale (0-5)

Suoritusvaatimukset

To complete the course, the student is required to (all three requirements must be completed to pass the course):
a) Execute the project work (20% of the final grade)
b) Execute the weekly exercises (1 per exercises lesson, 40% of the final grade)
c) Do the final exam (40% of the final grade)

Kohderyhmät

DI- ja arkkitehtiopiskelijat , International Students , Jatkotutkinto-opiskelijat

Exam Mon 04.05.2020 13:00 - 16:00

Oppimateriaali

Tyyppi Nimi Tekijä ISBN Lisätiedot Kieli Tenttimateriaali
Book An Introduction to Statistical Learning Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani English No
Book Statistics and Data Analysis for Microarrays Using R and Bioconductor Sorin Dr Introduction to the analysis of microarray data. English No