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Create a project

To create a project, select Projects from the side menu, then take the following actions:

  1. Click the Create New button on the upper right,
  2. give the project a Name and Description, and click Create and Open.

Create New Project

We previously discussed the difference between the global view and the project view. Notice that once you select a project, the user interface for the project view is in fact the same as for the global view, but now all of the left-side menu items are context dependent and specific to this project.

As for the global view, the following left-side menu items are available:

Files​

If you have not already done so, Add Data to the Data Assets.

  • If you Add Data from within the project, the data is owned by the project and no further action is necessary.
  • Otherwise, once your data is available in the Data Assets, Link to Project.

In the example displayed in the screenshot, the customer-churn-data has been added from within the Pyton project, and the project is the owner of the data, whereas the google-analytics data was added from within the global view and then linked to the Pyton project.

Read more: Files

Add Data

Connections​

Alternatively, your data source may be external, in a database or other cloud storage. The Connections menu item shows all the data connections available to the project. Click Create New to add a new one.

Read more: Connect to your data

Add connection dialog

Planning​

The Planning menu item implements an integration with Atlassian Jira and Confluence, de facto standards in project management.

Read more: Atlassian integration

Content​

Project workflow

Once your data is ready, you can take action within the Content menu item by clicking New:

  • Auto AI: Start Auto AI based on the data set.
  • Workflow Studio: Develop a workflow to visually transform, model, or score your data in a completely custom way.
  • Prompt Studio: Use Prompt Studio to create prompts and generate LLM-based responses.
  • App: Create an app to present your data, models and other results as a dashboard.

Workspaces​

Looking for a lightweight, but powerful source code editor to help you contribute Python code to your project?

A workspace provides exactly that: a source code editor, connected to a specific project. It runs in your browser and it comes with all the features you expect:

  • Code completion
  • Debuggers
  • Version control with Git
  • A large set of available extensions

Read more: Workspaces

Agents​

Leverage the power of Generative AI models directly inside the Workflow Designer and use them to create AI-based agents that can interact with the rest of the AI Cloud platform and of course with the outside world.

Read more:

Deployments​

With deployments, one can enable content created within the project to be integrated into existing business processes. This can happen in multiple ways, such as creating an automated schedule when a workflow should be executed, or exposing a workflow as a REST endpoint so that other applications can leverage it.

Read more: Deploy a project

Model Registry​

The Model Registry is the central place to store and manage machine learning models. It provides dedicated features for version tracking, labeling, and deployment management.

Read more: Model Registry

Coding environments​

Coding environments are self-contained language environments with packages and versions. In Altair AI Cloud, you can create code environments for Python. You can use them in notebooks, workspaces, and Execute Python operators in the workflow designer.

Read more: Coding environments

Details​

The Details menu item gives information about the project resources and resource usage, including:

  • which resource pool the project belongs to,
  • what resource quotas it has, and
  • if it is allowed to use GPU.

Read more: Resource management

Permissions​

The Permissions menu item makes it possible for you to invite other colleagues to work with you on the project. On the upper right, click Add User, select a User and Permission, and then click Submit.

  • Viewer - can read the project files, but not change them in any way
  • Contributor - can make changes, read and write to the project
  • Owner - has the right to delete the project

Read more: Access to data files

Project permissions