Course Player

AWS AI Learning Course

Read one exam-domain lesson, open the matching syllabus branch, then drill MCQs until the distractors are obvious.

  • Tracks 4 AWS AI paths
  • Lessons 18 Exam-domain modules
Now Studying

Deployment and Orchestration of ML Workflows (22%)

Select a lesson section to start.

0% 0%

Select a lesson section play button.

AWS Certified Machine Learning Engineer - Associate (MLA-C01)

Deployment and Orchestration of ML Workflows (22%)

This lesson turns the official MLA-C01 outline into a short preparation path. Read it once for orientation, then answer the linked MCQs from the syllabus branch before moving to the next module.

What To Master

Deploy, automate, and orchestrate ML pipelines, endpoints, batch jobs, and model lifecycle processes.

Fast Prep Tasks

  1. Select deployment patterns for real-time, asynchronous, serverless, and batch inference.
  2. Automate ML pipelines with repeatable build, test, approval, and release stages.
  3. Orchestrate dependencies across data, training, evaluation, and deployment.

AWS Services To Recognize

  • SageMaker Pipelines
  • SageMaker Endpoints
  • AWS Step Functions
  • AWS Lambda
  • Amazon ECR
  • AWS CodePipeline

Scenario Traps

  • Deploying a real-time endpoint when batch transform fits the latency and cost profile.
  • Skipping model registry, approval, or rollback needs in production workflows.

Speed Drill

After this lesson, open the matching syllabus branch and answer MCQs until you can explain why the wrong options are attractive but not best. Then run a short quiz with this module plus one previous weak module.

Official Source

Use the AWS exam guide as the source of truth for final scope checks: MLA-C01 exam guide.