Hello everyone! I hope this message finds you well. Whenever I open the lab, I came across this problem that my kernel is not connecting. It has connected for few labs but I am facing this problem again and again.
I have not changed my Ip address, as I am taking this course in my home.
I have no firewall security, that can interrupt kernel.
I have used the Jupyter notebooks previously and I have never faced such an issue.
Note: I have not shared the Lab number, because I am consistently facing this issue in many labs. Please help!
Hello SNaveenMathew,
I have also tried it! There’s no option to change the kernel. However, it shows python3, which I have selected. But, it has not been connected.
Stop and start the kernel:
3.a. Click File → Open. Ideally you’ll find one file with a green icon instead of orange indicating that the kernal is running. Ideally you’ll also find the file name in the “Running” tab:
3.b. If you find the kernel running and clicking File → Reconnect did not work in step 2, click Shutdown in the “Running” tab. Go back to Files - now the file will have an orange icon. Click the file to open a new kernel. Jupyter may ask you to choose a kernel as soon as you open the file.
I have already tried step 1 and 2. But, it didn’t work. I have also tried step 3. But, it still has same issues. The first lab was working fine, but all other labs are having same issues “Kernel Not Working”. However, I have downloaded the labs and practicing in my local VS code. Is it allowed? And, if I do homework using my local environment. And, upload it. Will there be any issue?
Yes, the issue is persistent for all of labs after lab 1 & 2. I have good internet and have cleared the browsing cache. Moreover, the issue is not with hard coding. Like, if I open a new lab that I have never opened before. It gives me the same error. I am unable to understand the issue. Previously, I have used the Jupyter notebook, but never came across this issue.
I have downloaded the labs to save my time. And, am working in local VS code. Is there an issue with it? Or, it’s all good?
Coursera grading requires the notebook to run on the assigned instance. As many mentors have pointed out, your notebook should run from start to finish and give the desired output on the hosted Jupyter notebook instance to be graded.
Final question - did your kernel die when you were executing a cell or was it dead from the very beginning? If it was the former, it’s possible that your script is exceeding the assigned resources (RAM/GPU/other) - this can be rectified by fixing the code that causes the resource overflow. If it’s the latter, and if shutting down and restarting the notebook didn’t work per step #3, something might’ve gone wrong with the Cloud notebook instance - this probably requires an escalation unless we’re able to solve it in a live session.
Working in the Coursera environment, there is no need to change the kernel.
Yes, very likely.
It’s extremely easy to mangle the metadata inside a notebook by downloading it to run on another platform, and then uploading it back to Coursera.
As @SNaveenMathew mentioned, one way for the kernel to stop is if your notebook outputs too much data to the console. If you added large print() statements for debugging, this can be a problem.
The kernel doesn’t die during executing a cell or due to any issues with hard-coded scripts. The kernel dies from the beginning. It never connects from the initial stage and am not able to execute the single cell. I don’t know how to solve this issue. Or where to contact Coursera as I have an assignment pending. I have performed the previous labs on local environments. But, as you have mentioned - we have to perform the code in the assigned instance. How can I resolve this issue?
can you please check into this issue. The learner is facing kernel error and not able to connect to kernel.
Such issue was noticed in short course but kernel error used to happen after kernel gets connected, and was told to ignore as it didn’t cause any issue running the codes. But in this learner’s case seems kernel is not connecting at all, and the screenshot shows kernel error.
Hi Muhammad. If the issue persists after TMosh’s suggestion above, please direct message me your Lab ID and the email you’re using for Coursera so we can investigate. Thank you.
