• Contents:

Rebranding Note

• ‼️  NOTE: in 2025, AWS rebranded SageMaker as "SageMaker AI”
  • If you're looking for it in the AWS Console, look for it under that new name
  • Just plain "SageMaker" currently takes you instead to "SageMaker Unified Studio" or the "SageMaker Platform," which is a wrapper around SageMaker and Amazon DataZone
  • The exam only covers SageMaker AI at this time. These notes only use “SageMaker”, and it should be understood as a synonym to “SageMaker AI”

Amazon SageMaker - Detailed Pages

Amazon SageMaker 101

SageMaker - Overview and Generic Features

SageMaker - Data Tools

SageMaker - Models and Humans

SageMaker - Governance

SageMaker Consoles

Amazon SageMaker Summary - Tools, Products, and Features

Ref: https://www.udemy.com/course/aws-ai-practitioner-certified/learn/lecture/44887795

• Amazon SageMaker: end-to-end ML service
• Generic features
  • SageMaker Automatic Model Tuning (AMT): tune hyperparameters
  • SageMaker Deployment & Inference: real-time, serverless, asynchronous, batch transform
  • SageMaker Studio: unified interface (IDE) for SageMaker
• Data Tools
  • SageMaker Data Wrangler: explore and prepare datasets, create features
  • SageMaker Feature Store: store features metadata in a central place
• Models and humans
  • SageMaker Clarify: compare models, explain model outputs, detect bias
  • SageMaker Ground Truth: RLHF, humans for model grading and data labeling
• Governance
  • SageMaker Model Cards: ML model documentation
  • SageMaker Role Manager: access control
  • SageMaker Model Dashboard: view all your models in one place
  • SageMaker Model Monitor: monitoring and alerts for your model
  • SageMaker Model Registry: centralized repository to manage ML model versions
  • SageMaker Pipelines: CICD for Machine Learning