Summary and Quiz on Data Quality, Labelling, and Governance

Explore how to build and manage reliable machine learning data pipelines using AWS services. Understand key techniques for validating data quality, implementing human-in-the-loop labeling with Ground Truth and Amazon A2I, detecting bias using SageMaker Clarify, and enforcing security with KMS, Lake Formation, and Macie. This lesson equips you to maintain dataset integrity, compliance, and fairness throughout the ML lifecycle.