AAIA Practice Test 5 — 10 Questions

Question 1

In SageMaker, what does 'Model Monitor' specifically detect?

Accepted Answer

Data and model drift. It monitors for data drift and model quality degradation in production.

Answer

Database uptime

Answer

Model size

Answer

Employee attendance

Question 2

What is the function of a 'Feature Store' in an MLOps pipeline?

Accepted Answer

Centralized feature serving and storage. A Feature Store provides a centralized repository for standardized feature definitions and storage for both training and inference.

Answer

Storing raw video files

Answer

Compressing model weights

Answer

Monitoring compute costs

Question 3

When auditing a Kubernetes-based AI deployment, what does a 'Pod Disruption Budget' (PDB) ensure?

Accepted Answer

Minimum availability during maintenance. Ensures that a minimum number of replicas are available during voluntary disruptions (e.g., node upgrades).

Answer

The model version

Answer

Maximum allowed CPU usage

Answer

The cost of the cluster

Question 4

In SageMaker, what is the role of an 'Endpoint Configuration'?

Accepted Answer

Defines model variants and compute resources. Defines the model, instance type, and traffic distribution (variants) for the production endpoint.

Answer

Defines the database password

Answer

Defines the data cleaning logic

Answer

Defines the training budget

Question 5

In a GCP Vertex AI pipeline, you want to ensure that every model artifact is associated with the specific training data and code version used. Which component provides this lineage tracking?

Accepted Answer

Vertex AI Metadata. Vertex AI Metadata tracks the lineage of artifacts throughout the lifecycle.

Answer

Feature Store

Answer

Vertex AI Pipelines

Answer

Vertex AI Experiments

Question 6

Which metric is commonly used to audit classification models?

Accepted Answer

F1-score. The F1-score balances precision and recall, providing a single metric for classification performance.

Answer

Logarithmic growth

Answer

Mean Squared Error

Answer

CPU utilization

Question 7

What is the primary benefit of using 'Containerization' for AI model auditability?

Accepted Answer

Environment reproducibility. Containerization packages an AI model along with its entire runtime environment—libraries, dependencies, and configuration files—into a single immutable image. This ensures that the model executes in exactly the same way regardless of where it is deployed, which is critical for auditability because auditors can reproduce the exact conditions under which a model was trained or inferred. Without such reproducibility, verifying model behavior or tracing decisions becomes unreliable due to environmental drift.

Answer

Reduced data storage costs

Answer

Increased hardware speed

Answer

Simplified UI design

Question 8

During an audit of an LLM pipeline, you discover that 'System Prompt' versioning is missing. What is the operational risk?

Accepted Answer

Unpredictable model behavior changes. Without system prompt versioning, changes to the instructions can cause unpredictable behavior changes that cannot be reverted.

Answer

Higher cloud bills

Answer

Increased latency

Answer

Database corruption

Question 9

Which of the following is a common 'drift' symptom an auditor should look for in production models?

Accepted Answer

Decreasing model accuracy. When data distribution changes (Concept Drift), the model's accuracy typically degrades over time.

Answer

Increasing server costs

Answer

Increased team size

Answer

Slow Git repository commits

Question 10

What is the primary objective of 'Board-level AI Governance'?

Accepted Answer

To ensure AI aligns with the organization's business strategy and risk appetite. Board-level AI governance exists to ensure that AI investments, deployments, and risks are aligned with the organization's strategic objectives and stated risk appetite. The board sets direction, approves risk tolerances, and holds management accountable — it does not perform engineering tasks. This strategic alignment function is what distinguishes governance from operational management.

Answer

To decide which programming language is used

Answer

To fix bugs in the model code

Answer

To organize the annual team lunch