Deck · AWS Machine Learning Engineer Associate
Data Preparation for ML and AI
AWS ML Engineer Associate (MLA-C02) Domain 1 — collecting and storing data, streaming ingestion, data formats, vector stores, Feature Store, transformation and feature engineering, embeddings, RAG document preparation, PII masking, FM training data, data quality, labeling, bias metrics, and class imbalance.
273 cards · SM-2 spaced repetition
Included with the full AWS Machine Learning Engineer Associate program — 4 decks, 968 cards.
Sample cards
Unlock the program to study all 273 cards with spaced repetition.
Cards are created from publicly available sources and may contain errors. Check anything you rely on against your official materials.
More in AWS Machine Learning Engineer Associate
Review data preparation for ml and ai — and the rest of AWS Machine Learning Engineer Associate.
One program. 968 cards across 4 decks.