Overview
271 real exam questions for the AWS Certified Machine Learning Engineer - Associate (MLA-C01).
The questions in my MLA-C01 YouTube videos come from this PDF. I only cover 20 to 30% of the bank publicly. This is the complete set, word for word.
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271 real exam questions - pulled from the actual MLA-C01 exam
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Instant delivery - sent to your email immediately after purchase
- Free updates every month, forever
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Full refund if you fail - no questions asked
Fail the MLA-C01 and it's another US$150 plus weeks of restudying. This PDF is US$39 - once, with a refund if you fail anyway.
Last updated: July 2026 - 271 questions
Deep Dive
The MLA-C01 is an MLOps exam wearing a machine learning badge. It doesn't ask you to derive algorithms - it drops you into a SageMaker workflow and asks how you'd prepare the data, deploy the endpoint, and keep the model honest in production.
Feature engineering and data preparation, SageMaker training and hyperparameter tuning, real-time versus batch versus serverless inference, model monitoring and drift detection, ML pipeline orchestration, IAM and VPC security for ML workloads. The calls a real ML engineer makes every day. Candidates strong in ML theory but weak on AWS operations consistently underperform - and vice versa. AWS doesn't test math, it tests which SageMaker capability fits the scenario, including the newer ordering and matching question formats.
65 questions. 130 minutes. 720 out of 1000 to pass. This PDF has 271 real questions from the actual MLA-C01 across all four domains - so the SageMaker-heavy scenarios, the new question formats, and the "most cost-effective" trade-offs are all familiar before you sit down.
If my free YouTube content is enough to pass, great. But if you want the full question bank before you sit down, this PDF is for you.
Exam Info
The MLA-C01 certifies ML engineers who build, deploy, and operationalize machine learning workloads on AWS - covering data preparation, model development, deployment, and monitoring - using Amazon SageMaker and the surrounding AWS data and security stack. No formal prerequisites, though 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, passing score 720/1000, US$150 per attempt, Pearson VUE testing centres and online proctored, valid 3 years.
