22-26 June 2020
Profund Innovation, Freie Universität Berlin - Altensteinstraße 40, 14195 Berlin, Germany
The use of modern quantitative technologies to characterize complex phenomena represents the standard procedure in almost every research domain.
Biology makes no exception and the use of multi-omics techniques (metabolomics, transcriptomics, genomics and proteomics) is pervasive in every facets of life sciences. The resulting multivariate
datasets are highly complex and advanced data analysis approaches have to be applied in order to optimize the information retrieved. For relatively large scales investigations, machine learning
represents a valid tool to complement classical multivariate statistical methods.
The objective of the course is to highlight advantages and limitations of these type of approaches in the context of biological research, providing a broad hands-on introduction to the use of multivariate methods and machine learning for the analysis of complex datasets.
The syllabus has been planned for people with zero or very basic knowledge of machine learning. Students are assumed to have basic familiarity with a programming language (Python, R, Matlab, ...)
The course is delivered over ten half-day sessions (see details below). Each session consists of a lecture of two hours followed by one hour of practical exercises/demonstration. There will also be plenty of time for students to discuss their own problems and data.
Monday- 09:30- 17:30
COURSE + REFRESHMENTS
COURSE + REFRESHMENTS + LUNCH and ACCOMMODATION
Please click HERE to get all the information about our packages.
Registration deadline: 20th May 2020
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.