271 practice questions for AWS Certified Machine Learning Engineer, Associate (MLA-C01), with full explanations.
Every question comes with the correct answer, the reasoning behind it, and a note on why each wrong option is wrong. Work through it once with the answers, then again with the questions-only copy under exam conditions.
- 271 questions across all four MLA-C01 domains
- Answers and explanations for every question, including the wrong options
- A questions-only PDF for timed practice runs
- Instant delivery by email the moment you check out
- Free monthly updates for as long as the exam is live
- Pass or your money back
A failed MLA-C01 attempt costs another US$150, plus the time it takes to restudy. This pack is US$39, paid once, and refunded if you fail.
Try 10 questions free before you buy.
Last updated September 2026 · 271 questions
What makes the MLA-C01 hard
MLA-C01 is an MLOps exam wearing a machine learning badge. It does not ask you to derive algorithms; it drops you into a SageMaker workflow and asks how you would prepare the data, deploy the endpoint and keep the model honest in production. Feature engineering, SageMaker training and hyperparameter tuning, real-time versus batch versus serverless inference, model monitoring and drift detection, ML pipeline orchestration, and IAM and VPC security for ML workloads are the calls a real ML engineer makes every day.
65 questions in 130 minutes, 720 out of 1000 to pass. This pack has 271 practice questions across all four domains, so the SageMaker-heavy scenarios, the newer question formats and the cost-effectiveness trade-offs are familiar before you sit down.
About the exam
MLA-C01 certifies ML engineers who build, deploy and operationalise machine learning workloads on AWS, covering data preparation, model development, deployment and monitoring with Amazon SageMaker and the surrounding AWS data and security stack. AWS recommends at least one year of ML engineering experience. Valid for three years.
Exam domains
- Data preparation for machine learning: 28%
- ML model development: 26%
- Deployment and orchestration of ML workflows: 22%
- ML solution monitoring, maintenance, and security: 24%
65 questions, 130 minutes, pass mark 720 out of 1000, US$150 per attempt, Pearson VUE test centres or online proctored, valid for three years.
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