AI Azure AI Engineer 2

Question 1

Which Azure service provides a managed environment for training and deploying machine learning models at scale?

Accepted Answer

Azure Machine Learning

Answer

Azure Machine Learning is the fully managed platform for the end-to-end ML lifecycle including training, deployment, and monitoring.

Question 2

In Azure Cognitive Services, which API would you use to extract key phrases and sentiment from customer reviews?

Accepted Answer

Text Analytics API

Answer

Text Analytics API (now part of Azure AI Language) provides sentiment analysis, key phrase extraction, and named entity recognition for text.

Question 3

What is the purpose of an Azure Machine Learning compute cluster compared to a compute instance?

Accepted Answer

Compute clusters scale to zero when idle and support parallel jobs; compute instances are single-node development VMs

Answer

Compute clusters auto-scale nodes up and down for batch/parallel training jobs, while compute instances are always-on single-node VMs for development.

Question 4

Which deployment option in Azure AI Foundry allows you to host an open-source model like Llama 3 on dedicated infrastructure?

Accepted Answer

Managed compute endpoint

Answer

Managed compute endpoints provision dedicated GPU infrastructure to host open-source models, giving you full control over the runtime.

Question 5

When building a RAG (Retrieval-Augmented Generation) solution on Azure, which service is typically used to store and search document embeddings?

Accepted Answer

Azure AI Search

Answer

Azure AI Search (formerly Cognitive Search) provides vector search capabilities that enable semantic retrieval of document chunks for RAG pipelines.

AI - Engineer Practice Test

AI - Engineer Practice Test

AI Azure AI Engineer 2