SGN-54106 Computational Diagnostics, 5 cr

Lisätiedot

Suitable for postgraduate studies.

Vastuuhenkilö

Frank Emmert-Streib, Susanna Ketola

Osaamistavoitteet

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 and business intelligence. 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 experiments and business processes, e.g., the stock market or consumer behavior. 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 and business problems, i.e., the adaptation of machine learning methods in a problem specific manner.

Sisältö

Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi

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)

Arvosteluasteikko:

Numerical evaluation scale (0-5)

Osasuoritukset:

Completion parts must belong to the same implementation

Oppimateriaali

Tietoa esitietovaatimuksista
Basic programming skills. Experience with the language R are desirable, but not necessary. Basic knowledge in Mathematics and Machine Learning. Basic knowledge of biology/systems biology.

Vastaavuudet