Vocareum Notebook
Written by Kevin Wesley
Updated over a week ago

Modern Vocareum lab types are in general release. Please contact support@vocareum.com to set up a compatible course.

Vocareum Notebook is our flagship, cloud-based Jupyter notebook built to empower educators with streamlined task automation and advanced budget governance for GPU training and OpenAI credits.

Creating a Vocareum Notebook Lab

From the course page select "Edit Assignment" and "New Assignment"

Create a name for the assignment and select your lab type. In this case "Vocareum Notebook". Press "Save and continue".

Now that your first Part has been created, return to the Assignment settings. Under Actions select Configure Workspace to begin uploading coursework to your assignment.

Configure Workspace and Releasing Data

Selecting "Configure Workspace" will open the "teacher view". Instructors can upload and test coursework, upload datasets, and release work to learners from here.

Upload your Jupyter Notebook file to /startercode and when ready select Update to release your coursework to learner workareas.

To release large data sets to learners, place your files in the voc/data/ directory. This will create a read-only copy of your data file to be released to the learner's workarea.

Enabling GPU and OpenAI functionality

From the Part settings, navigate to Resources and you will find the options to turn enable GPU Execution and OpenAI API Key Generation.

GPU settings allow control over budget over time in minutes.

OpenAI settings allow budgeting over OpenAI use for each learner. When the budget is enabled learners will automatically have a Vocareum-managed OpenAI api key, without them having to create their own account.

Student View

Instructors have the ability to view, interact and troubleshoot their Vocareum Notebook as a student would, using the Student View feature.

Student view:

Learner Experience

When a learner opens their lab they will be presented with a work area such as below

File Browser

Learners will access coursework and data from the file tree.

All work placed in /startercode will be delivered to learners in their /work directory

View Submissions

Selecting this folder will allow learner's to view previous submissions they have made in the lab.

View Budget and Details

When using OpenAI selecting the first icon will display the OpenAI details. Including an up to date budget, as well as API Base and API Key.

Selecting the second icon will display GPU details and time budget for that learner's lab.

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