1. Where are the labs?
2. How do I access the labs?
3. Why are the labs locked? I don’t see a “Launch App” button.
4. I clicked the
Start Lab button but it’s taking a while for the AWS button to turn green. What should I do?
5. How do I download the notebooks?
6. How do I submit the labs or mark them as completed?
7. I got logged out and saw an “AWS account deactivated” message. What does it mean?
8. I see a “Budget exceeded”/“AWS account deactivated”/“Account is still in cleanup” message when I click “Start Lab”. How do I solve this?
9. I’m getting an
InvalidSignatureException with a “Signature expired” message. What should I do?
10. The kernel fails to start, and there is a popup showing an
AccessDeniedException. What does this mean?
11. Why is the kernel crashing while training the model?
12. I’m sure that I selected the correct instance type but the kernel doesn’t start right away. I just see “Starting notebook kernel” at the top. What should I do?
13. Why do I get this error: Module Not Found Error: No module named ‘torch._C’?
14. I’m getting a
ResourceLimitExceeded error when I select
ml.m5.2xlarge. What does it mean?
15. I can’t find the
ml.m5.2xlarge option when selecting the instance type. Where is it?
1. Where are the labs?
You can see the labs in the classroom items right after the walkthrough videos by Chris Fregly. There should be one lab per week.
At the bottom of the App Item containing the labs, you should tick the checkbox stating you agree to uphold the Coursera Honor Code. Then, click on the
Launch App button. This will open a new tab in Vocareum that contains instructions to run the AWS lab.
If nothing happens after clicking
Launch App, please check your browser’s pop-up blocker. Also check that your browser has enabled cookies and cross-site tracking. These are needed because the Vocareum lab environment is embedded into the Coursera site. You can read more about that here.
There is also a known bug when trying to run the labs on some tablets. We recommend running them on a desktop or laptop.
The labs are available to non-audit enrollees. It is also not covered by Coursera Plus. If you purchased the course and they are still locked, please contact Coursera through chat or email (instructions here) so they can check your account.
The labs should start within 30 minutes (usually less). If the countdown timer starts, the button usually turns green before it reaches 1:30. If it takes longer than that, please reply to this topic so we can investigate and escalate if needed.
You can either right-click on the file in the File Explorer, or click
File in the Menu Bar. Both should have a
right-click the filename in the File Explorer:
You can click the
Submit button in the upper right of the Vocareum instructions page. There is no Submit button in Sagemaker or the AWS console. Also take note that the button will only work after you have successfully started the lab (i.e. after the AWS light turns green and you click on it).
The lab provisions a studio app by default. In order to combat fraud and excessive charges, if you try to launch additional studio apps (or any resources outside the scope of the lab), the platform will deactivate your access. You can fill out this form , and our partners will work on re-enabling your access. It is best to avoid this case by being mindful of the bounds of the lab.
In most of the learner reports, this is related to the instance type selected for the kernel. Please check point 10 below to see how you can check if you’re using the correct one to avoid deactivation.
Please fill out this form so our team can investigate your account. We will reach out to you when you can retry the lab. This is usually resolved within the day but please wait 48 hours (excluding weekends and US holidays) before following up.
Please check your operating system’s clock and sync it to a time server if possible? Here’s one article for reference but feel free to find another resource based on your setup. Then, relaunch the lab from the classroom.
You might be using a different instance type for the notebook environment. Please use the instance in the screenshot in the notebook. As of this writing, that is
ml.m5.2xlarge but please double-check. In the notebook settings, you might have to scroll further down to the “All Instances” section to find it. Make sure that you’re selecting
ml.m5.2xlarge and not
ml.m5.large. After doing so, you can verify by hovering over the kernel button. It should show the instance type like below:
If you’re using something else, the kernel might not start, or if it does, it might crash later on.
Please see the answer above for question #10.
This happens sometimes, and we’ve reported it to our partners so they can investigate. If you’re sure that you’ve selected the correct instance type (as mentioned in question #10 above), you can wait several minutes until the notebook kernel starts. The delay can range from 5 to 40 minutes, but it should eventually start. Kindly report here when this happens so we can escalate to our partners.
There are two things to check here. First, select the correct instance type as mentioned in item 10 above. After that, make sure to run the
pip install cells before running the import cells. These are usually the first code cells in the notebook. It might print out some errors but it should be acceptable. You can go back to Chris Fregly’s walkthrough videos in the classroom to check the expected output.
The initial popup will only show around four instance type options at the top. Please scroll further down the “All Instances” section to find