Mastering R for Epidemiologic Research | Online Course | Starting 27 April 2026 💻📊
The online course Mastering R for Ep...
Mastering R for Epidemiologic Research | Online Course | Starting 27 April 2026 💻📊
The online course Mastering R for Epidemiologic Research begins on 27 April 2026 and offers a flexible, fully asynchronous learning experience for researchers, public health professionals, epidemiologists, and clinicians who want to strengthen their R programming skills.
Led by Malcolm Barrett, data scientist and research software engineer at Stanford University, the course introduces modern tools from the R ecosystem, including the Tidyverse and Quarto, and supports participants in building reproducible, high-quality analyses.
Participants will learn to: • Master the tidyverse for readable, efficient, and reproducible data science workflows • Create dynamic, fully reproducible documents with Quarto (exportable to PDF, HTML, Word, and more) • Model statistical problems using linear and logistic regression
🗓 Format & Schedule
Asynchronous online course (50 virtual seats)
Materials available from 27 April
Equivalent to a one-week, 40-hour intensive course
Flexible completion within one to four weeks (final submission deadline: 26 May)
The course combines structured teaching units with optional advanced materials for those wishing to dive deeper into programming and reproducible research. Participants completing four assignments can earn ECTS credit or receive a certificate of participation.
All materials are provided online and remain accessible after the course.
Registration is available via the official online form.
Mastering R for Epidemiologic Research | Online Course | Starting 27 April 2026 💻📊
The online course Mastering R for Epidemiologic Research begins on 27 April 2026 and offers a flexible, fully asynchronous learning experience for researchers, public health professionals, epidemiologists, and cli...
Mastering R for Epidemiologic Research | Online Course | Starting 27 April 2026 💻📊
The online course Mastering R for Epidemiologic Research begins on 27 April 2026 and offers a flexible, fully asynchronous learning experience for researchers, public health professionals, epidemiologists, and clinicians who want to strengthen their R programming skills.
Led by Malcolm Barrett, data scientist and research software engineer at Stanford University, the course introduces modern tools from the R ecosystem, including the Tidyverse and Quarto, and supports participants in building reproducible, high-quality analyses.
Participants will learn to: • Master the tidyverse for readable, efficient, and reproducible data science workflows • Create dynamic, fully reproducible documents with Quarto (exportable to PDF, HTML, Word, and more) • Model statistical problems using linear and logistic regression
🗓 Format & Schedule
Asynchronous online course (50 virtual seats)
Materials available from 27 April
Equivalent to a one-week, 40-hour intensive course
Flexible completion within one to four weeks (final submission deadline: 26 May)
The course combines structured teaching units with optional advanced materials for those wishing to dive deeper into programming and reproducible research. Participants completing four assignments can earn ECTS credit or receive a certificate of participation.
All materials are provided online and remain accessible after the course.
Registration is available via the official online form.
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