diff --git a/FAQ.Rmd b/FAQ.Rmd
index ea0ca03c..7dd48b3b 100644
--- a/FAQ.Rmd
+++ b/FAQ.Rmd
@@ -245,4 +245,3 @@ Here are some great Aalto courses that are using Bayesian inference
 - [CS-E5795 - Computational Methods in Stochastics](https://mycourses.aalto.fi/course/info.php?id=40704) (more about MC, MCMC, HMC)
 - [MS-E1654 - Computational Inverse Problems](https://mycourses.aalto.fi/course/info.php?id=40592)
 - Bayesian workflow course (spring 2024, we'll advertise later in BDA Zulip)
-- Self study or reading circle: O'Hagan & Forster, Bayesian Inference (any time, contact Aki Vehtari)
diff --git a/project.Rmd b/project.Rmd
index a0a93f6a..979fd4a4 100644
--- a/project.Rmd
+++ b/project.Rmd
@@ -213,9 +213,9 @@ As some data sets have been overused for these particular goals, note that the
 following ones are forbidden in this work (more can be added to this list so
 make sure to check it regularly):
 
-  - extremely common data sets like titanic, mtcars, iris
+  - extremely common data sets like titanic, mtcars, iris, penguins (Palmer Archipelago, n=344)
   - Baseball batting (used by Bob Carpenter's StanCon case study).
-  - Data sets used in the course demos
+  - Data sets used in the course demos like bodyfat, diabetes, 
 
 It's best to use a dataset for which there is no ready made analysis in internet, but if you choose a dataset used already in some online case study, provide the link to previous studies and report how your analysis differs from those (for example if someone has made non-Bayesian analysis and you do the full Bayesian analysis).