AWS Certified Machine Learning Engineer - Associate (MLA-C01)

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.

Content outline:

• 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)

Click here for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) Live Online Training Details,