A HANDS-ON COURSE ON MACHINE LEARNING FOR GENOMICS
The general aim of the course is to equip participants with practical and technical knowledge to deploy machine learning methods on genomic data sets, such as statistical concepts and unsupervised and supervised machine learning methods to analyze high-dimensional data sets.
There will be theoretical lectures followed by practical sessions where students directly apply what they have learned.
The course will be beneficial for first year computational biology PhD students, and experimental biologists and medical scientists who want to begin data analysis or are seeking a better understanding of computational genomics and analysis of popular sequencing methods.
The course is open for anyone who is interested in the subjects we are teaching.
Here is a link to an article about the 2015 course.
Application deadline: 30 June 2021
More information here