Facultative Module for medical students WS 20/21: Data Analysis and Visualization in R

Medicine students can register for the course ONLY in TUMonline, the course can be easily found by searching for IN2339 in "Lehrveranstaltungen". course description: This facultative courses teaches methodologies and good practice of data science using R. The lecture is structured into three main parts, covering the major steps of data analysis:

1. Get the data: how to fetch, and manipulate real-world datasets. How to structure them ("tidy data") to most conveniently work with them.

2. Look at the data: basic and advanced visualization techniques (grammar of graphics, unsupervised learning) will allow students to navigate and identify interesting signal in large and complex datasets and formulate hypotheses.

3. Conclude: concepts of statistical testing will allow concluding about the raised hypotheses. Also methods from supervised learning will allow to model data and build accurate predictors. Each week, the lecture is accompanied with exercises. During the exercises, combinations of the concepts seen during the lecture will allow performing more involved data analysis tasks. Students generate report that embed code and analysis. Two more advanced case studies complement the course. Many examples will stem from applications in genomics, but no pre-requisite in this domain is necessary.