The AWS Certified Machine Learning Engineer – Associate (MLA-C01) validates that you can build, operationalise, deploy and maintain machine-learning solutions and pipelines on AWS — primarily with Amazon SageMaker AI and supporting data, security and DevOps services. It targets people with roughly one year of hands-on ML experience. This module is independent prep over the public AWS exam guide and is not an official AWS course or the certification exam.

FOUR CONTENT DOMAINS The exam is scored across Data Preparation for ML (28%), ML Model Development (26%), Deployment & Orchestration of ML Workflows (22%), and ML Solution Monitoring, Maintenance & Security (24%). Weightings tell you where to spend study time.

28%Data Prep

26%Model Dev

22%Deploy/Orch

24%Monitor/Sec

The exam is about 65 questions over 130 minutes, using multiple-choice and multiple-response formats. The result is reported pass/fail on a scaled score of 100-1,000 with 720 to pass; the registration fee is $150 USD.

🧮~65 questions

⏱️130 minutes

🎯720 to pass

💵$150 fee

EXAM TIP Read each scenario for the constraint that decides the answer — latency, cost, scale, real-time vs batch, security, or least operational effort. AWS questions are usually "which service fits these constraints best", not "what is the definition".

📈 AWS Machine Learning Engineer – Associate (MLA-C01)