Meta menu:

From here, you can access the Emergencies page, Contact Us page, Accessibility Settings, Language Selection, and Search page.

Open Menu

Intensive Short Courses at the BSPH

Participants in the Intensive Short Courses (ISC) acquire in-depth knowledge with a methodological focus on a specialized topic in public health and epidemiology.

The ISCs are aimed at PhD students and students from public health master's programs and external participants from Germany and abroad and professionals.

Past courses are listed in the archive.

 

You are here:

Intensive Short Courses:

  • are held in cooperation with lecturers from renowned universities and research institutes from Germany and abroad
  • are part of the postgraduate programs offered by the Institute of Public Health at Charité - Universitätsmedizin Berlin
  • usually offered in English
  • award ECTS credits
  • require a performance assessment

Places are allocated according to the date of registration (first come first serve).

Unfortunately we are unable to offer funding assistance. Please contact scholarship opportunities such as DAAD directly to see if they have funding available.

Intensive Short courses 2021

ONLINE Malcolm Barrett: Mastering R for Epidemiologic Research, March 08 - March 12, 2021

Advanced Epidemiologic Methods: Mastering R for Epidemiologic Research

ASYNCHRONOUS ONLINE COURSE, 40 (virtual) seats

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.

Date: March 08 - March 12, 2021

Lecturer: 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.

Learning objectives:

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.

Pre-requisites:

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  

Materials:

R is a free open source programming language and tool for statistics. For the hands-on exercises, you can either use RStudio Cloud (advantage: “plug-and-play”, no need to install anything) or download and install the most recent version of R (https://www.r-project.org/) as well as RStudio (https://rstudio.com/products/rstudio/download/).

About the online format:

  • This is an asynchronous online course. The course consists of 40 teaching units of material organized into 5 full workdays (8 units / hours of student investment time per workday).
  • Course material will be made available on Friday, March 5th and will remain available through Monday, March 22nd, 2021. An office hour to help with access and setup will be available on Friday, March 5th from 4-5pm. 
  • Live office hour support will be provided every day between Monday, March 8th and Friday, March 12th from 4-5pm by the Instructor, Malcolm Barrett (based in Los Angeles) as well as from 10-11am by the TA, Sebastian Hinck. The office hours are optional. 

    • Students who can devote a full work day to the class should be able to complete all the required work in the first week and can hand in their proof of achievement on Monday, March 15, 2021. 
    • Students may opt to complete the course over the course of two weeks. However, office hour support will only be available on March 15th, 17th and 19th from 10-11am with Sebastian Hinck in the second week. The last opportunity for students to hand in their proof of achievement is Monday, March 22, 2021. 

  • Course material will be available via Blackboard.
  • Students will need to complete and submit 4 assignments (online) in order to recieve ECTS credit. If you only want a certificate of participation, you will need to submit all assignments showing reasonable effort (i.e. at least 20 points to “pass”).
  • To maximize flexibility all around, the course will be entirely asynchronous. That is, students can work entirely at their own pace. The content is equivalent to a one week, 40 hour, full-time course with 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 are less advanced can skip these sections.

Course Information:

  • Course language: English
  • ECTS points: 3
  • Course Fee: 510€ for students, 750€ for other participants

Registration:

Please use the registration form or send an e-mail to Tanja Te Gude

Tel. +49 30 450 570 812

ONLINE Malcolm Barrett: Mastering R for Epidemiologic Research, August 16 - August 20, 2021

Advanced Epidemiologic Methods: Mastering R for Epidemiologic Research

ONLINE COURSE, 40 (virtual) seats

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.

Date: August 16 - August 20, 2021

Lecturer: 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.

Learning objectives:

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.

Pre-requisites:

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  

Materials:

R for Data Science (https://r4ds.had.co.nz/) and Advanced R, ed. 2 (https://adv-r.hadley.nz/), both free online.

About the online format:

  • The course starts Monday, August 16th and will run for 1 week until Friday, August 20th 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 1 week after the course ends. 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 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 week of the ISC 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 Information:

  • Course language: English
  • ECTS points: 3
  • Course Fee: 510€ for students, 750€ for other participants

Registration:

Please use the registration form or send an e-mail to Tanja Te Gude

Tel. +49 30 450 570 812

Please complete the form to sign up for a course:

Registration Intensive Short Courses










This could also be of interest: