AWS Certified Machine Learning Engineer - Associate (MLA-C01)
Associate-level certification that validates technical ability in implementing ML workloads in production and operationalizing them. For individuals with at least 1 year of experience using Amazon SageMaker and other AWS services for ML engineering, along with at least 1 year of experience in a related role such as backend software developer, DevOps developer, data engineer, or data scientist.
What the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam covers
Domains and their approximate weight on the exam.
Data Preparation for Machine Learning (ML)
28%Ingest and store data. Transform data and perform feature engineering. Ensure data integrity and prepare data for modeling.
ML Model Development
26%Choose a modeling approach. Train and refine models. Analyze model performance.
Deployment and Orchestration of ML Workflows
22%Select deployment infrastructure based on existing architecture and requirements. Create and script infrastructure based on existing architecture and requirements. Use automated orchestration tools to set up continuous integration and continuous delivery (CI/CD) pipelines.
ML Solution Monitoring, Maintenance, and Security
24%Monitor model inference. Monitor and optimize infrastructure and costs. Secure AWS resources.
How CertSim helps you pass
Realistic questions
Scenario-based questions aligned to the official AWS Certified Machine Learning Engineer - Associate (MLA-C01) objectives.
AI explanations
Understand why each answer is right or wrong, with deep-dive explanations.
Readiness analytics
Track your score by domain and know when you are ready for exam day.
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