Why This Cheat Sheet Matters for MLA-C01
This cheat sheet covers the most important SageMaker Model Monitor 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. Study data quality, model quality, bias drift, explainability drift, baselines, monitoring schedules, and alerting for deployed models. Use this as a quick-reference guide during your final review sessions.
2Sections
8Key Points
Monitoring Types
- Data quality monitoring compares incoming data to a baseline schema and distribution.
- Model quality monitoring compares predictions to ground truth labels when available.
- Bias drift checks whether bias metrics change over time.
- Explainability drift checks whether feature attribution changes over time.
Operational Pattern
- Create a baseline from representative data.
- Capture production inference data.
- Schedule monitoring jobs.
- Send violations to CloudWatch and trigger review or retraining.
Practice Model Monitor Questions
Put your knowledge to the test with practice questions.