change link and add course formats

index.Rmd

@@ -20,7 +20,7 @@ knitr::write_bib(c(
 
 # About this Course {-}
 
-This course is part of a series of courses for the [Informatics Technology for Cancer Research (ITCR)](https://itcr.cancer.gov/) called the Informatics Technology for Cancer Research Education Resource. This material was created by the ITCR Training Network (ITN)  which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant:  [National Cancer Institute (NCI)](https://www.cancer.gov/)  UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at [www.itcrtraining.org](www.itcrtraining.org) for more information.
+This course is part of a series of courses for the [Informatics Technology for Cancer Research (ITCR)](https://www.cancer.gov/about-nci/organization/cssi/research/itcr) called the Informatics Technology for Cancer Research Education Resource. This material was created by the ITCR Training Network (ITN)  which is a collaborative effort of researchers around the United States to support cancer informatics and data science training through resources, technology, and events. This initiative is funded by the following grant:  [National Cancer Institute (NCI)](https://www.cancer.gov/)  UE5 CA254170. Our courses feature tools developed by ITCR Investigators and make it easier for principal investigators, scientists, and analysts to integrate cancer informatics into their workflows. Please see our website at [www.itcrtraining.org](www.itcrtraining.org) for more information.
 
 Considerations for Bioinformatic Data Visualization is the first in a series of two courses on data visualization. This course focuses on considerations for best practices in data visualization discussing topics such as
  - defining what data visualization is
@@ -30,4 +30,9 @@ Considerations for Bioinformatic Data Visualization is the first in a series of
  - making visualizations accessible
  - avoiding data distortions
 
- The second course in the series will focus on building data visualizations, pointing to resources across R and Python, while integrating the best practice considerations discussed in this course.   
+ The second course in the series will focus on building data visualizations, pointing to resources across R and Python, while integrating the best practice considerations discussed in this course.
+
+ # Available Course Formats {-}
+
+ - The material for this course can be viewed without login requirement on this [Bookdown website](https://hutchdatascience.org/DataViz_Considerations/). This format might be most appropriate for you if you rely on screen-reader technology.
+ - Our courses are open source, you can find the [source material for this course on GitHub](https://github.com/fhdsl/DataViz_Considerations/).