Set up your Python Machine Learning Bootcamp seamlessly by uploading your course files directly to Google Drive and connecting with Google Colab. Learn how to correctly structure your folders to avoid file path errors.
Key Insights
- Upload the entire "Python Machine Learning Bootcamp" folder directly into the "My Drive" directory on Google Drive without adding additional subfolders to ensure correct file path configurations.
- Use Google Drive's "Folder Upload" option (not "File Upload") to efficiently upload all 101 necessary course files in one action.
- After initial setup, Python notebooks stored in Google Drive will automatically open in Google Colab, simplifying future access and workflow.
Note: These materials offer prospective students a preview of how our classes are structured. Students enrolled in this course will receive access to the full set of materials, including video lectures, project-based assignments, and instructor feedback.
Now that you've got your first Jupyter notebook open, let's get all of the other Jupyter notebooks, as well as the data files and images that we'll need in this course, uploaded to Google Drive and easily openable in Google Colab. So the way we're going to do that is you're going to go to Google Drive, this is my Google Drive home, and you're going to navigate from there on the left-hand side over here to My Drive. When you do that, you're going to upload your whole folder to this My Drive.
Now, it's very important that it be in My Drive, that My Drive should be here at the top with no other folders. We want to upload directly to My Drive, and that's because all of our file paths in our notebooks assume that, that this is the location for your Python Machine Learning Bootcamp folder. I'll show you that at work.
We're going to upload this folder. We'll go over to the left here in Drive to New, and Folder Upload, not File Upload, Folder Upload. We're going to upload the whole folder at once.
So make sure that your... It should open up a little dialog box like this. Make sure that Python Machine Learning Bootcamp is the selected folder. Don't be as I actually was when I opened this.
Don't have Start or Final selected or any of those. You want the selected part to be Python Machine Learning Bootcamp, the whole folder. And then you're going to choose Upload.
It might say Select Folder here. You should trust the site and upload all 101 files. Now, it's going to take a moment, but we won't wait for it.
Python Machine Learning Bootcamp here should be the folder, should be the name of the folder in My Drive. All of our folders will... All of our files will assume that you have a Python Machine Learning Bootcamp folder in My Drive directly. Once those are all uploaded, you should be able to... We could probably get started that way.
You should be able to go into the Start folder, and there is a... Here's the one we've already got open, but let's open it this way. We'll be able to open all of them in this way from now on without having to individually do any of it. We'll just go to Google Drive, navigate to the folder, and just double-click on that file.
And now that we've connected Google Drive and Google Colab when we ran this line initially, now that we've done that once, it's automatically set to open up any Python notebooks in Google Drive from now on. So again, the only thing to be careful of in this setup is to make sure that in My Drive, you have a folder called Python Machine Learning Bootcamp, and then all of our files are directly in there. And that, again, it should be... The path should be My Drive, and then Python Machine Learning Bootcamp with no other folders in between.
Don't make another folder and put Python Machine Learning Bootcamp in there. Very easy thing to do. Try to organize things.
It's already organized for you, and adding another layer of organization will mean you'll have to do a lot more work on all the Jupyter notebooks to make sure that the file paths work. All right, that's your setup, getting all of our files into your system. We are now going to be able to jump back and talk about what a Python notebook is and start working with them.