- Understand the role of data science in their discipline - Use R and Rstudio to explore different datasets - Apply basic criteria and tools to transform and visualise their data - Interpret their data based on the results of an exploratory data analysis (EDA)
Prerequisiti
None
Metodi didattici
Class activity will be focused to demonstrations, discussions and problem solving through interaction: demo, group work, quiz and real-time feedback. Containers (docker), virtual machines and code editors will be used in classes, to improve learning R and the other command-line tools used in the course
Verifica Apprendimento
Multiple choice quiz
Testi
- R Bioinformatics Cookbook Dan MacLean Packt Publishing, 2019 - Modern Statistics for Modern Biology Holmes, Susan; Huber, Wolfgang
Contenuti
This course is aimed at a medical and life science audience, with no prior background of data analysis and a minimal background of statistics. The goal of the course is to provide students with the most important tools and decision criteria, to import and visualise data originating from different sources (structured medical data, laboratory measures, biological experiments), to explore and understand key elements in those datasets they might encounter in their studies or everyday practice. Classes will include: - R and Rstudio: introduction tour and hands-on (part 1) - R and Rstudio: introduction tour and hands-on (part 2) - Import your data in R and make sense of it - What are "tidy" data, and why should you care - Data types: examples and applications - That bit of statistics you cannot avoid - Applied examples of data analysis - Data lab: bring your own data or suggest some