Comparing lossless versus lossy compression for Windows users

episodes/02-image-basics.md

@@ -881,20 +881,22 @@ two orders of magnitude smaller than the bitmap version.
 ## Comparing lossless versus lossy compression (optional, not included in timing)
 
 Let us see a hands-on example of lossless versus lossy compression.
-Once again, open a terminal and navigate to the `data/` directory.
+Open a terminal (or Windows PowerShell) and navigate to the `data/` directory.
 The two output images, `ws.bmp` and `ws.jpg`, should still be in the directory,
 along with another image, `tree.jpg`.
 
 We can apply lossless compression to any file by using the `zip` command.
 Recall that the `ws.bmp` file contains 75,000,054 bytes.
 Apply lossless compression to this image by executing the following command:
-`zip ws.zip ws.bmp`.
+`zip ws.zip ws.bmp` 
+(`Compress-Archive ws.bmp ws.zip` with PowerShell).
 This command tells the computer to create a new compressed file,
 `ws.zip`, from the original bitmap image.
-Execute a similar command on the tree JPEG file: `zip tree.zip tree.jpg`.
+Execute a similar command on the tree JPEG file: `zip tree.zip tree.jpg` 
+(`Compress-Archive tree.jpg tree.zip` with PowerShell).
 
 Having created the compressed file,
-use the `ls -al` command to display the contents of the directory.
+use the `ls -l` command (`dir` with PowerShell) to display the contents of the directory.
 How big are the compressed files?
 How do those compare to the size of `ws.bmp` and `tree.jpg`?
 What can you conclude from the relative sizes?

episodes/03-skimage-images.md

@@ -187,10 +187,10 @@ Don't forget to use `fig, ax = plt.subplots()` so you don't overwrite
 the first image with the second.
 Images may appear the same size in jupyter,
 but you can see the size difference by comparing the scales for each.
-You can also see the differnce in file storage size on disk by
+You can also see the difference in file storage size on disk by
 hovering your mouse cursor over the original
-and the new file in the jupyter file browser, using `ls -l` in your shell,
-or the OS file browser if it is configured to show file sizes.
+and the new files in the Jupyter file browser, using `ls -l` in your shell 
+(`dir` with Windows PowerShell), or viewing file sizes in the OS file browser if it is configured so.
 
 :::::::::::::::  solution
 

learners/setup.md

@@ -132,4 +132,8 @@ e.g. your Desktop or a folder you have created for using in this workshop.
 
    :::::::::::::::::::::::::
 
+5. A small number of exercises will require you to run commands in a terminal. Windows users should 
+use PowerShell for this. PowerShell is probably installed by default but if not you should
+[download and install](https://apps.microsoft.com/detail/9MZ1SNWT0N5D?hl=en-eg&gl=EG) it.
+
 [figshare-data]: https://figshare.com/articles/dataset/Data_Carpentry_Image_Processing_Data_beta_/19260677