AWS Machine Learning Engineer – Associate

The AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam validates a candidate’s ability to build, operationalize, deploy, and maintain machine learning (ML) solutions and pipelines by using the AWS Cloud.

This exam validates a candidate's ability to complete the following tasks:

  • Ingest, transform, validate, and prepare data for ML modeling.
  • Select general modeling approaches, train models, tune hyperparameters, analyze model performance, and manage model versions.
  • Choose deployment infrastructure and endpoints, provision compute resources, and configure auto scaling based on requirements.
  • Set up continuous integration and continuous delivery (CI/CD) pipelines to automate orchestration of ML workflows.
  • Monitor models, data, and infrastructure to detect issues.
  • Secure ML systems and resources through access controls, compliance features, and best practices.

Who Should Take This Exam?

The target candidate should have at least 1 year of experience using Amazon SageMaker and other AWS services for ML engineering. The target candidate also should have at least 1 year of experience in a related role such as a backend software developer, DevOps developer, data engineer, or data scientist. Recommended general IT knowledge:

  • Basic understanding of common ML algorithms and their use cases
  • Data engineering fundamentals, including knowledge of common data formats, ingestion, and transformation to work with ML data pipelines
  • Knowledge of querying and transforming data
  • Knowledge of software engineering best practices for modular, reusable code development, deployment, and debugging
  • Familiarity with provisioning and monitoring cloud and on-premises ML resources
  • Experience with CI/CD pipelines and infrastructure as code (IaC)
  • Experience with code repositories for version control and CI/CD pipelines

Steps to Achieve Your AWS Certified Machine Learning Engineer - Associate Certification

  1. Attend AWS Technical Essentials
  2. Attend DevOps Engineering on AWS
  3. Attend Practical Data Science with Amazon SageMaker
  4. Attend MLOps Engineering on AWS Training Course
  5. Pass the following exams:
  • Exam MLA-C01

AWS Data Engineer Associate Bootcamp - Specialty: Course

AWS Technical Essentials

In just one day, this instructor-led training introduces you to core AWS concepts, services, and terminology.

Enroll Now
1 Day | $695

AWS Data Engineer Associate Bootcamp - Specialty: Course

DevOps Engineering on AWS

DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools.

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3 Days | $2025

AWS Data Engineer Associate Bootcamp - Specialty: Course

Practical Data Science with Amazon SageMaker

In this one-day, hands-on course, you’ll learn how to build, train, and deploy machine learning models using Amazon SageMaker.

Enroll Now
1 Day | $675

AWS Data Engineer Associate Bootcamp - Specialty: Course

MLOps Engineering on AWS

MLOps Engineering on AWS is a hands-on, instructor-led course that helps you bring structure, automation, and scale to your ML workflows.

Enroll Now
3 Days | $2025

Exam Guide and Practice Questions

AWS Certification Renewal

  • Certification through AWS is valid for three years from the date it was earned. Before the three-year period expires, you must recertify to keep your certification current and active.
  • To keep your certification active, you must take the current version of the exam that corresponds to your certification before it expires. AWS does not require or accept other methods of recertification, such as continuing education credits.
  • For Foundational and Associate level certifications, you can also satisfy the recertification requirement for a current certification by passing or recertifying with a higher-level role-based exam.

Learn more about the AWS recertification.