Events by this organizer

https://nci.rev.vbrick.com/#/videos/9db0a539-5bf2-4bc2-9e07-523161137e6e

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
This is very important! Please follow this link and install https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule

Register

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and install https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule

Register

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and install https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule

Register

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule

Register

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule

Register

The goal of these workshops is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and https://rstudio-education.github.io/hopr/starting.html onto your computer before class. If you have trouble doing this please send email to ncibtep@nih.gov and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

For more information and class updates, please see the GitHub page for the class at https://abcsfrederick.github.io/Intro-to-R-Fall2020/Schedule