Managing Projects in
Cloudera AI
Managing Projects
Creating a Project with ML Runtimes variants
Creating a project from a password-protected Git repo
Configuring Project-level Runtimes
Adding Project Collaborators
Modifying Project settings
Managing Project Files
Deleting a Project
Native Workbench Console and Editor
Launch a Session
Run Code
Access the Terminal
Stop a Session
Workbench editor file types
Environmental Variables
Third-party Editors
Modes of configuration
Configure a browser-based IDE as an Editor
Testing a browser-based IDE in a Session
Configuring a browser-based IDE at the Project level
Configuring a local IDE using an SSH gateway
Configure PyCharm as a local IDE
Add Cloudera AI as an Interpreter for PyCharm
Configure PyCharm to use Cloudera AI as the remote console
(Optional) Configure the Sync between Cloudera AI and PyCharm
Configure VS Code as a local IDE
Download cdswctl and add an SSH Key
Initialize an SSH connection to Cloudera AI for VS code
Setting up VS Code
(Optional) Using VS Code with Python
(Optional) Using VS Code with R
(Optional) Using VS Code with Jupyter
(Optional) Using VS Code with Git integration
Limiting files in Explorer view
Git for Collaboration
Linking an existing Project to a Git remote
Embedded Web Applications
Example: A Shiny Application
Example: Flask application