Ausschließlich für Fachpublikum
Intensive Short Course online, Aug 31 - Sept 12, 2020
The course is for researchers, public health professionals, epidemiologists, and clinicians who want to improve their R coding skills, who want to learn modern tools in the R ecosystem, like the tidyverse and Shiny, or who want to get started writing software in R.
At the end of the course, participants will have:
- Mastered the tidyverse, a set of principled tools for data science. The tidyverse is a friendly, readable, and fast set of packages intended to work well together, to improve code readability, and to make analyses more reproducible.
- Written dynamic documents using best practices for reproducible research, including using R Markdown. R Markdown intertwines code and text so that reports and articles are fully reproducible and exportable to PDF, HTML, Word, and more. R Markdown also has excellent support for citation management and formatting for journals.
- Modeled simple statistical and causal problems using both classical regression (linear, logistic) and G-methods.
- Written robust functions, programmed with functions, and created a basic R package.
- Built ready-to-share web applications entirely in R using the Shiny framework.
Basic epidemiology and statistics. Some experience with R programming will be helpful, but those new to R can take a free introductory course on DataCamp: https://www.datacamp.com/courses/free-introduction-to-r
About the online format:
- The course starts Monday August 31st and will run for 2 weeks with instructor/TA support
- Course material will be linked from Blackboard
- Students will need to complete and submit 4 assignments (online) for credit. We will allow submissions of the assignments up to 3 weeks from the course start date. Students can therefore work through the course at an even slower pace (also on the weekends, if desired), just being aware that the office hour support will only run the first two weeks. For those who still prefer the compact format, it is of course also possible to finish the course within 1 week.
- To maximize flexibility all around, the course will be entirely asynchronous. That is, students can work entirely at their own pace. The content will be equivalent to the 1 week, full-time course (3 ECTS). Some content will be clearly marked as “optional” for those who want to take a “deeper dive”, seek additional examples and/or want to learn more advanced programming skills. Those who have less time could skip these sections.
- During the 2-week period starting Aug 31st, on weekdays, Malcolm Barrett would hold regular office hours (via Zoom) in the early morning Los Angeles time, end of work day Berlin time (exact time TBD). Teaching assistants (Berlin-based) would offer office hours earlier in the day.
- Course language: English
- ECTS points: 3
- Course Fee: 510€ for students, 750€ for other participants
Tel. +49 30 450 570 812
Malcolm Barrett, MPH
Malcolm Barrett is a PhD candidate in epidemiology at the University of Southern California. He studies vision loss and eye diseases that affect vision, like diabetic retinopathy. Specifically, he works on methods to improve the study of how vision impacts quality of life, including tools from psychometrics and causal inference, to make vision-specific quality of life analyses more accurate and more interpretable. In addition to applied research, Malcolm also develops R packages for epidemiologic and biostatistical methods, teaches R, and organizes the Los Angeles R Users Group. He regularly contributes to open source software, including favorite community projects like ggplot2 and R Markdown.
Berlin School of Public Health
Institute of Public Health, Charité - Universitätsmedizin Berlin
9:00h - 17:00h
Charité Campus Virchow