Why This Cheat Sheet Matters for MLA-C01
This cheat sheet covers the most important Amazon SageMaker AI concepts tested on the MLA-C01 (AWS Machine Learning Engineer Associate) certification exam. It contains 2 sections with 8 key points that you should memorize before exam day. Prepare for SageMaker training jobs, processing jobs, notebooks, pipelines, endpoints, model registry, Studio, and managed ML workflows. Use this as a quick-reference guide during your final review sessions.
2Sections
8Key Points
Key Building Blocks
- Processing jobs transform and validate data before training.
- Training jobs run built-in algorithms or custom containers.
- Model Registry stores versions, metadata, approval status, and deployment readiness.
- Endpoints host models for real-time, serverless, or asynchronous inference.
Exam Cues
- Need repeatable ML workflow: SageMaker Pipelines.
- Need systematic hyperparameter search: automatic model tuning.
- Need detect drift after deployment: SageMaker Model Monitor.
- Need cost-optimized interruptible training: managed spot training.
Practice SageMaker Questions
Put your knowledge to the test with practice questions.