Exam Details
AWS · MLA-C01
Prepare for MLA-C01: Build, train, deploy, and operationalize ML models on AWS using SageMaker.
Overview
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FAQ
The MLA-C01 certification validates your ability to build, train, deploy, and maintain machine learning solutions on AWS. This associate-level certification targets ML engineers who perform exploratory data analysis, feature engineering, model training, and MLOps using Amazon SageMaker. You'll demonstrate skills in data engineering for ML, modeling with built-in algorithms and frameworks, and implementing ML pipelines for production. As organizations operationalize ML at scale, engineers who bridge data science and production deployment are essential to every ML team.
You're a fit for MLA-C01 if you:
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| Domain | Weight | What This Means |
|---|---|---|
| Data Engineering for ML | 20% | Build data ingestion pipelines, perform feature engineering, and manage datasets for ML workflows |
| Exploratory Data Analysis | 24% | Analyze distributions, handle missing data, detect outliers, and select features for model training |
| Modeling | 28% | Select algorithms, train and tune models, evaluate performance, and apply SageMaker built-in tools |
| ML Implementation and Operations | 28% | Deploy models to endpoints, implement CI/CD for ML, monitor drift, and manage model lifecycle |
You're probably ready if you can:
You might need more prep if:
If this feels too advanced:
If you know the basics but want to build confidence:
The exam consists of 65 questions to be completed within 130 minutes. These questions are presented in two formats:
The exam is scored on a scale of 100 to 1,000, with a minimum passing score of 720. To ensure you are ready for the challenge, ExamOS offers scenario-based practice quizzes that build real exam confidence by simulating the complexity of the actual test environment.
The exam content is divided into four main domains that reflect the lifecycle of a machine learning project:
Successful candidates typically use a combination of official and community resources:
The registration fee for the AWS Certified Machine Learning Engineer - Associate exam is $150 USD. Please note that additional taxes may apply based on your local jurisdiction and the test center location.
If you are unsuccessful on your first attempt, you must wait 14 calendar days before you are eligible to retake the exam. There is no limit on the number of attempts you can make, but you must pay the full registration fee for each subsequent attempt.
The certification is valid for three years from the date you pass the exam. To maintain your certified status, you must go through the recertification process, which typically involves:
This certification is intended for individuals who have at least one year of experience in building, deploying, and maintaining ML solutions on AWS. While there are no formal prerequisites to take the exam, the target audience includes:
The demand for professionals who can bridge the gap between data science and production engineering is at an all-time high. Holding this certification can lead to several high-value roles:
Once you have mastered the Associate level, you can further specialize your skill set with these related AWS certifications: