Pre-work

Before we get started, we will download some assets and complete some setup for our workshop. This section is broken up into the following steps:

1. Download Workshop Assets

Various parts of this workshop will require the attendee to upload files or run scripts. These artifacts have been collected in the following zip file which you can download by clicking the link below and saving the zip file locally to your machine.

Note: The analytics project zip file does not to be unzipped/expanded. It will be directly uploaded to the Cloud Pak for Data platform as a zip file. For reference, all these assets are also in the GitHub repo for this workshop.

2. Create a Project and Deployment Space

At this point of the workshop we will be using Cloud Pak for Data for the remaining steps.

  • Launch a browser and navigate to your Cloud Pak for Data deployment.

NOTE: Your instructor will provide a URL and credentials to log into Cloud Pak for Data!

Cloud Pak for Data login

Create a New Project

In Cloud Pak for Data, we use the concept of a project to collect / organize the resources used to achieve a particular goal (resources to build a solution to a problem). Your project resources can include data, collaborators, and analytic assets like notebooks and models, etc.

  • Go the (☰) navigation menu and under the Projects section click on All Projects.

(☰) Menu -> Projects
  • Click on the New project button on the top right.

Start a new project
  • Select the Analytics project radio button and click the Next button.

New analytics project
  • We are going to create a project from an existing file (which contains the assets we will use throughout this workshop), as opposed to creating an empty project. Select the Create a project from a sample or file option.

Create project from file
  • Click on the browse link and in the file browser pop-up, navigate to where you downloaded the CreditRiskProject.zip file in the previous section, then click the open button.

Browse for project files
  • Give the project a name and click the Create button.

Project name
  • From the project creation succesfully created pop up window, click on the View new project button.

Import project success

Create a Deployment Space

Cloud Pak for Data uses the concept of Deployment Spaces to configure and manage the deployment of a set of related deployable assets. These assets can be data files, machine learning models, etc.

  • Go the (☰) navigation menu and click Deployments.

(☰) Menu -> Analytics deployments
  • Click on the New deployment space button.

Add New deployment space
  • We will create an empty deployment space, so click on the Create an empty space option.

Create empty deployment space
  • Give your deployment space a unique name, optional description, then click the Create button.

Deployment space name
  • From the deployment space creation pop up window, click on the View new space button.

Import project success
  • Next, we will add a collaborator to the new deployment space. Collaborators allow others to view/edit/manage the assets being deployed. In this workshop, we want the models we deploy to be visible and monitored in the OpenScale model monitoring lab.

  • Click on the Access control tab and then click on Add collaborators on the right.

Deployment space access control
  • Enter "admin" as a Collaborator input field and select the Admin user from the drop down list. Then click on the Add to list button.

Deployment space collaborators

NOTE: We are adding the user that configured the machine learning instance for OpenScale monitoring. In this case, the user is the admin user.

  • Click the Add button to finish adding the collaborator. You should be brought back to the deployment space page and see your user ID along with the Admin user as collaborators for this space.

Conclusion

We've completed creating the project and deployment space that we will be using for the rest of this workshop.