diff --git a/05-data-visualization.Rmd b/05-data-visualization.Rmd
index eeae576..02e14ba 100644
--- a/05-data-visualization.Rmd
+++ b/05-data-visualization.Rmd
@@ -32,7 +32,7 @@ Categorical (between 1 categorical and 1 continuous variable)
 
 -   Violin plots
 
-[![Image source: Seaborn's overview of plotting functions](https://seaborn.pydata.org/_images/function_overview_8_0.png)](https://seaborn.pydata.org/tutorial/function_overview.html)
+[![Image source: Seaborn\'s overview of plotting functions](https://seaborn.pydata.org/_images/function_overview_8_0.png)](https://seaborn.pydata.org/tutorial/function_overview.html)
 
 Why do we focus on these common plots? Our eyes are better at distinguishing certain visual features more than others. All of these plots are focused on their position to depict data, which gives us the most effective visual scale.
 
@@ -180,6 +180,10 @@ plot = sns.displot(data=metadata, x="Age", hue="Sex", multiple="dodge", palette=
 
 ```
 
+## Other resources
+
+We recommend checking out the workshop [Better Plots](https://hutchdatascience.org/better_plots/), which showcase examples of how to clean up your plots for clearer communication.
+
 ## Exercises
 
 Exercise for week 5 can be found [here](https://colab.research.google.com/drive/17iwr8NwLLrmzRj4a6zRZucETXpPkmDNR?usp=sharing).
diff --git a/config_automation.yml b/config_automation.yml
index 460f418..b54e4df 100644
--- a/config_automation.yml
+++ b/config_automation.yml
@@ -27,4 +27,4 @@ make-book-txt: yes
 
 # What docker image should be used for rendering?
 # The default is jhudsl/base_ottr:main
-rendering-docker-image: 'jhudsl/base_ottr:main'
+rendering-docker-image: 'jhudsl/ottr_python:main'