AWS Certified Machine Learning Engineer – Associate (MLA-C02) Practice Tests: 9 Practice Tests and 585 Questions
MLA-C02
585
Data Preparation for ML and AI | Data ingestion, vector databases, embeddings, feature engineering, data quality checks and bias detection (28%)
ML Model and Foundation Model (FM) Development | Model selection, foundation model customization, fine-tuning, RAG design and model evaluation (24%)
Deployment and Orchestration of ML and AI Workflows | SageMaker endpoints, Bedrock agents, knowledge bases, CI/CD pipelines and MLOps automation (24%)
Operating, Monitoring, and Securing ML and AI Solutions | Model monitoring, agent observability, cost optimization, IAM security and Bedrock Guardrails (24%)
Data Preparation for ML and AI
A legal firm is ingesting long contracts into an Amazon Bedrock knowledge base. Questions usually target a specific clause, but good answers need the surrounding section for context. Small chunks retrieve precisely but lose context, and large chunks retrieve poorly. Which chunking strategy should the ML engineer choose?
No chunking, so each contract is a single chunk
Fixed-size chunking with 20-token chunks and no overlap
Hierarchical chunking, which matches small child chunks and returns their larger parent chunks
Removing all section headings before fixed-size chunking
C
Hierarchical chunking embeds small child chunks for precise matching, then returns each match's larger parent chunk, so the model gets the specific clause together with its surrounding section. One chunk per contract retrieves imprecisely, tiny fixed-size chunks lose meaning, and removing headings throws away useful structure.
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Course Content
Supporting Resources
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AWS MLA-C02 – Practice Test #1
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AWS MLA-C02 – Practice Test #2
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AWS MLA-C02 – Practice Test #3
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AWS MLA-C02 – Practice Test #4
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AWS MLA-C02 – Practice Test #5
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Exam Mode: AWS MLA-C02 – Practice Test #6
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AWS MLA-C02 – Practice Test #7
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AWS MLA-C02 – Practice Test #8
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AWS MLA-C02 – Practice Test #9
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