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

ONLINE COURSE, 50 (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 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, March 8th and will run for 1 week until Friday, March 12th 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

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

Advanced Epidemiologic Methods: Mastering R for Epidemiologic Research

ONLINE COURSE, 50 (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: