MLA-C01: Exam Objectives
For the complete and official list of exam objectives, refer to the official exam guide:
AWS Certified Machine Learning Engineer - Associate Exam Guide (PDF)
Exam Weighting
| Domain | Weight | Focus Areas |
|---|---|---|
| Domain 1: Data Preparation for ML | ~28% | Ingest, store, transform, feature engineering, data integrity |
| Domain 2: ML Model Development | ~26% | Model selection, training, tuning, performance analysis |
| Domain 3: Deployment and Orchestration | ~22% | Infrastructure, containers, CI/CD pipelines |
| Domain 4: Monitoring, Maintenance, Security | ~24% | Model monitoring, cost optimization, security |
In-Scope AWS Services
Machine Learning
- Amazon SageMaker: End-to-end ML platform (primary focus)
- SageMaker Studio, Data Wrangler, Feature Store
- SageMaker Pipelines, Model Registry
- SageMaker Clarify, Model Monitor, Debugger
- SageMaker JumpStart, Autopilot, Neo
- SageMaker Inference Recommender
- Amazon Bedrock: Foundation models and fine-tuning
- Amazon A2I: Human review workflows
- Amazon Comprehend: NLP and text analysis
- Amazon Rekognition: Image and video analysis
- Amazon Textract: Document extraction
- Amazon Transcribe: Speech-to-text
- Amazon Translate: Language translation
- Amazon Personalize: Recommendations
- Amazon Forecast: Time-series forecasting
- Amazon Q: AI-powered assistant
Analytics & Data
- AWS Glue: ETL and data catalog
- AWS Glue DataBrew: Visual data preparation
- Amazon EMR: Big data processing (Spark)
- Amazon Athena: Serverless SQL queries
- Amazon Kinesis: Real-time streaming
- AWS Lake Formation: Data lake management
- Amazon Redshift: Data warehouse
Compute & Containers
- Amazon EC2: Compute instances (GPU/CPU)
- AWS Lambda: Serverless functions
- AWS Batch: Batch processing
- Amazon ECR: Container registry
- Amazon ECS/EKS: Container orchestration
Developer Tools & CI/CD
- AWS CodePipeline: CI/CD pipelines
- AWS CodeBuild: Build service
- AWS CodeDeploy: Deployment automation
- AWS CloudFormation: Infrastructure as code
- AWS CDK: Cloud Development Kit
Monitoring & Management
- Amazon CloudWatch: Monitoring and logging
- AWS CloudTrail: API audit logging
- AWS X-Ray: Distributed tracing
- AWS Cost Explorer: Cost analysis
- AWS Compute Optimizer: Resource rightsizing
Storage
- Amazon S3: Object storage (primary data lake)
- Amazon EFS: Shared file storage
- Amazon FSx: High-performance file systems
- Amazon EBS: Block storage
Security
- AWS IAM: Identity and access management
- AWS KMS: Key management
- Amazon Macie: Data security
- AWS Secrets Manager: Secrets management
Study Progress
MLA-C01 Study Progress
0/50%
💾 Progress is saved in your browser's local storage. Clearing your browser data will reset your progress.