AWS Machine Learning Engineer - Associate (MLA-C01) — Practice Questions and Mock Exam

The AWS Certified Machine Learning Engineer – Associate validates the ability to build, train, deploy, and maintain machine learning models in production on AWS. It covers data preparation for ML, model development and tuning, deployment and orchestration of ML workflows, and monitoring and securing ML solutions using services like SageMaker.

This certification is designed for ML engineers, data scientists, and MLOps practitioners with at least one year of experience using AWS ML services. It demonstrates proficiency in operationalizing ML models, building automated training pipelines, and implementing responsible AI practices in production environments.

The exam consists of 65 questions (50 scored, 15 unscored) over 130 minutes, featuring multiple-choice, multiple-response, ordering, and matching question types. Questions focus on SageMaker workflows, model training, hyperparameter tuning, deployment strategies, and ML pipeline automation. With roughly 2.6 minutes per question, take time to reason through complex scenarios.

This exam tests ML engineering — not data science theory. Candidates must understand how to operationalize models on AWS using SageMaker, automate ML pipelines, and implement monitoring rather than just build notebooks.

Delivered via Pearson VUE online or at testing centers. Available in English; additional languages may be added over time. The certification is valid for 3 years with renewal through recertification exams.