In the era of “Big Data”, Biological/Biomedical Sciences’ data, be it from laboratory, clinical or population studies, is also getting increasingly voluminous and complex. Traditional mathematical and statistical methods, although fundamental, are not always suited for visualizing and extracting information from complex multi-dimensional data and turn-key solutions/software are typically limited in scope and applicability. Not surprisingly, the ability to implement hands-on/custom computational solutions to transform, find patterns in and interpret complex data is becoming a highly valued skill in both academia and industry. However, it is very hard for the biological/biomedical experimental scientist, at all levels of academic education, to find available courses/tutorials that can cover such complex topics without prior advanced background. This course aims precisely at filling that gap: to provide a solid basic background and intense hands-on experience in concepts and methodologies of Computational Data Analysis applied to biological/biomedical experimental data, without requiring any prior advanced knowledge.

This 7-day hands-on advanced course is intended for undergraduate, Master and PhD students, and researchers of biological/biomedical fields who may have basic knowledge of statistics and data analysis but want to learn the basics of fundamental advanced computational techniques to analyze large complex data sets. The hands-on tutorials will focus on exploratory data analysis of real experimental data generated at the Life and Health Science Research Institute (ICVS), but the methodologies being taught can be applied to any type of experimental data. The goal of this course is to provide biological/biomedical scientists with knowledge and confidence to implement custom tools to analyze and interpret complex multi-dimensional data generated in their own experiments.