Navigate Amazon SageMaker Unified Studio
Amazon SageMaker Unified Studio provides a comprehensive integrated development environment for machine learning (ML) and data science workflows. For SageMaker Unified Studio domains configured with IAM roles, you will be able to access the following components from the project overview page.
Navigation Panel
The left sidebar contains hierarchical navigation to access various Amazon SageMaker Unified Studio interfaces organized by:
Overview
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Files: Browser interface for local file system storage and S3 buckets.
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Data: Browser interface for catalog asset management
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Connections: Centralized view for all compute and data connections
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Notebooks: Serverless notebook interface
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Workflows: Orchestrate jobs and tasks
Data analytics
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Query Editor: Dedicated SQL interface.
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Visual ETL: Visual interface for Extract, Transform, Load operations
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Data processing jobs: View and manage job execution
AI/ML
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Models: Jump start into available models – foundation and registered.
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MLflow: Manage machine learning lifecycles
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Training jobs: Managing model training processes
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Inference endpoints: Deployment and endpoint management
Integrated development environments (IDEs)
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JupyterLab: Managed JupyterLab integrated development environment
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Editor for VS Code: Visual Studio Code integrated development environment
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Code spaces: Create and manage multiple individually configured development environments. For more information, see Code spaces in Amazon SageMaker Unified Studio.
Domain Management
For IAM roles with administrator privileges to access the admin interface
Jump into your data and models
This top section provides quick access to common actions:
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Explore your data - Explore and analyze data using SQL
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Build in the notebook - Prepare data for analytics or to train and deploy machine learning models
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Discover ML models – Discover, deploy and manage models
Build with sample data
This section middle section offers pre-configured example projects:
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Customer usage analysis - SQL-based customer retention analysis
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Customer segmentation - PySpark and AWS Glue analysis
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Customer churn prediction - Random Forest implementation with feature engineering
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Retail sales forecasting - End-to-end retail sales analysis using Amazon SageMaker Unified Studio AI
Change the display mode
Amazon SageMaker Unified Studio defaults to your operating system's display preference (light or dark mode). You can override this setting to choose a specific mode.
To change the display mode
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In the upper-right corner of the console, choose the profile icon.
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Choose Customize appearance.
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Select one of the following options:
System. Uses your operating system's light or dark mode setting.
Light. Always displays in light mode.
Dark. Always displays in dark mode.
Your preference is saved automatically and applied across sessions.
Change the display language
Amazon SageMaker Unified Studio supports 12 languages. By default, your preferred language is automatically detected based on your browser's default language settings. You can override this setting to choose a specific language.
Supported languages:
English (American)
Chinese (Simplified)
Chinese (Traditional)
French
German
Indonesian
Italian
Japanese
Korean
Portuguese (Brazilian)
Spanish
Turkish
To change the display language
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In the upper-right corner of the console, choose the profile icon.
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Choose Language selector.
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Select your preferred language from the list.
Your preference is saved automatically and applied across sessions. The selected language applies across all pages within Amazon SageMaker Unified Studio.
Note
The following areas are not yet translated and display content in English:
In IAM-based domains: the Browse page in the Catalog and MLflow.
In Identity Center-based domains: ML Pipelines and MLflow.
