Use automated orchestration tools to set up continuous integration and continuous delivery (CI/CD) pipelines.
5 practice questions under this official exam objective (MLA-C01), each with the answer key, an option-by-option explanation and instant feedback.
Questions under this objective
5 total · page 1 of 1Orchestrating SageMaker ML Workflows as DAGs in Studio with ML Lineage Tracking for Govern
Data scientists need fine-grained control of the ML workflows they orchestrate, must visualize SageMaker jobs and workflows as a directed acyclic grap
How Do You Require Manual Approval Before SageMaker Model Deployment?
A SageMaker Model Registry approval status gate is how you enforce a manual review before any model version reaches a production endpoint. This page c
Integrating AWS Glue Jobs into SageMaker Pipelines with a Callback Step
AWS Glue data processing jobs already exist and are orchestrated by a Glue workflow, and the new SageMaker Pipelines must consume their output during
Enforcing a Manual Model Approval Gate in a SageMaker Pipeline Before Production Deploymen
A company building a SageMaker-based web application must implement a manual approval-based workflow so that only approved models can be deployed to p
AWS SageMaker CI/CD Pipeline Automation with S3 Events
This guide explains how to automate an AWS SageMaker ML pipeline triggered by new data uploads using Amazon S3 event notifications, CodePipeline, and