[sib-courses] SIB course - Introduction to Machine Learning, 22 - 23 July 2020, streamed

Monique Zahn Monique.Zahn at sib.swiss
Wed May 27 10:02:41 CEST 2020


Dear all,

We are pleased to announce the following SIB course on:

*Introduction to Machine Learning, 22 - 23 July 2020, streamed**. *

With the rise in high-throughput sequencing technologies, the volume of 
omics data has grown exponentially in recent times and a major issue is 
to mine useful knowledge from these data which are also heterogeneous in 
nature. Machine learning (ML) is a discipline in which computers perform 
automated learning without being programmed explicitly and assist humans 
to make sense of large and complex data sets. The analysis of complex 
high-volume data is not trivial and classical tools cannot be used to 
explore their full potential. Machine learning can thus be very useful 
in mining large omics data sets to uncover new insights that can advance 
the field of bioinformatics.

This 2-day course will introduce participants to the machine learning 
taxonomy and the applications of common machine learning algorithms to 
omics data. The course will cover the common methods being used to 
analyze different omics data sets by providing a practical context 
through the use of basic but widely used R libraries. The course will 
comprise a number of hands-on exercises and challenges where the 
participants will acquire a first understanding of the standard ML 
processes, as well as the practical skills in applying them on familiar 
problems and publicly available real-world data sets.

Further detailed information, prerequisites and application form are 
available here 
<https://www.sib.swiss/training/course/2020-07-machine-learning>.

Should you have any questions, please don't hesitate to contact us at 
training at sib.swiss.

Have a nice day,

Monique

**--
***Monique Zahn, PhD
SIB Training
* *SIB | Swiss Institute of Bioinformatics*
Quartier Sorge, Bâtiment Amphipôle - 1015 Lausanne - Switzerland
monique.zahn at sib.swiss - www.sib.swiss ****


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