Andrew, thanks for following up!
Indeed, I confirmed that simply updating FastaiSageMakerStack template doesn’t reinstall conda environment properly. The issue persists since even though the updated stack has the solution that you recommended it needs to be activated.
After some poking around I got your solution to work! Here’s the procedure I used for anyone who is facing the same issue (I assume it applies to many folks installing fastai2 course in SageMaker now):
- Modify the FastaiSageMakerStack template per AndrewN’s single line solution as noted above.
- Save the modified stack template f.e. in the AWS S3 bucket and save the address (url) of the template for the next steps.
- Delete the existing FastaiSageMakerStack (this wipes out all provisioned resources including the corrupt install of conda environment that caused the issue. You have the modified template stored and that’s all you need for the next step).
- Create a new stack from scratch using the same parameters as specified here: Amazon SageMaker | Practical Deep Learning for Coders (naming the stack FastaiSageMakerStack etc).
- Select the existing stack template option and enter the stack template url (generated in step 2). Create the stack.
- Complete Jupyter Notebooks deployment per the course instructions. The above should have installed your conda environment smoothly making fastai available as an option for Notebook kernel.
Hope this helps! Now on to the course - let’s build and train some models! 
Best
PO