Compendium Centrum Edukacyjne

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.

The exam also 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.

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 AWS knowledge

The target candidate should have the following AWS knowledge:

• Knowledge of SageMaker capabilities and algorithms for model building and deployment
• Knowledge of AWS data storage and processing services for preparing data for modeling
• Familiarity with deploying applications and infrastructure on AWS
• Knowledge of monitoring tools for logging and troubleshooting ML systems
• Knowledge of AWS services for the automation and orchestration of CI/CD pipelines
• Understanding of AWS security best practices for identity and access management, encryption, and data protection

Domains & Competencies

• Domain 1: Data Preparation for Machine Learning (ML) (28% of scored content)
• Domain 2: ML Model Development (26% of scored content)
• Domain 3: Deployment and Orchestration of ML Workflows (22% of scored content)
• Domain 4: ML Solution Monitoring, Maintenance, and Security (24% of scored content)

Detailed described domains, list of specific tools and technologies that might be covered on the exam, as well as lists of in-scope AWS services https://d1.awsstatic.com/training-and-certification/docs-machine-learning-engineer-associate/AWS-Certified-Machine-Learning-Engineer-Associate_Exam-Guide.pdf 

Exam overview

Level: Associate

Length: 130 minutes to complete the exam

Cost: 150 USD (*when purchasing directly from AWS)

Visit Exam pricing for additional cost information.

Format: 65 questions; either multiple choice or multiple response

Delivery method: Pearson VUE testing center or online proctored exam.