Cheat Sheet Poster

episodes/02-image-basics.md

@@ -32,6 +32,12 @@ as numeric abstractions, approximations of what we see with our eyes in the real
 Before we begin to learn how to process images with Python programs,
 we need to spend some time understanding how these abstractions work.
 
+:::::::::::::::::::::::::::::::::::::::::  callout
+
+Feel free to make use of the [available cheat-sheet](./files/cheatsheet.html) as a guide for the rest of the course material. View it online, share it, or print the [PDF](./files/cheatsheet.pdf)!
+
+::::::::::::::::::::::::::::::::::::::::::::::::::
+
 ## Pixels
 
 It is important to realise that images are stored as rectangular arrays

instructors/instructor-notes.md

@@ -36,6 +36,12 @@ to share your experience with the lesson Maintainers.
 - Be aware that learners might get surprising results in the *Keeping only low intensity pixels* exercise, if `plt.imshow` is called without the `vmax` parameter.
   A detailed explanation is given in the *Plotting single channel images (cmap, vmin, vmax)* callout box.
 
+## Additional resources
+
+- A cheat-sheet with graphics illustrating some concepts in this lesson is available:
+    - [Cheat-sheet HTML for viewing in browser](../episodes/files/cheatsheet.html). 
+    - [PDF version for printing](../episodes/files/cheatsheet.pdf).
+
 
 ## Questions from Learners