AWS Certified Machine Learning Engineer - Associate Study Guide

Preparing for the AWS Certified Machine Learning Engineer – Associate (MLA-C02) exam? Study tip: use this study guide to review exam topics.

The exam validates your ability to build, operationalize, deploy, and maintain AI and ML solutions and pipelines on AWS. When studying a team, a dataset or a live system, focus on which option meets the stated requirements rather than assuming the least change, the least build effort or the narrowest control is always best. Check each option against the stated requirements. You might weigh a ready-made AWS AI service against training your own model in Amazon SageMaker AI, or a prompt and retrieval change against fine-tuning a foundation model. Generative AI runs through every domain, from vector stores and chunking to agents and guardrails.

The exam has four official content domains, each with its own weighting. Data Preparation for ML and AI leads at 28%, and model development, deployment and orchestration, and operating, monitoring and securing ML and AI solutions carry 24% each.