AI-100 Online Practice Questions and Answers

Correct Answer: B

You need to enable Model data collection.

References: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-data-collection

Correct Answer: ABC

Remote computing is available for specific data sources on selected platforms. The following tables document the supported combinations. RxInSqlServer, sqlserver: Remote compute context. Target server is a single database node (SQL

Server 2016 R Services or SQL Server 2017 Machine Learning Services). Computation is parallel, but not distributed.

RxSpark, spark: Remote compute context. Target is a Spark cluster on Hadoop.

RxLocalParallel, localpar: Compute context is often used to enable controlled, distributed computations relying on instructions you provide rather than a built-in scheduler on Hadoop. You can use compute context for manual distributed

computing.

References:

https://docs.microsoft.com/en-us/machine-learning-server/r/concept-what-is-compute-context

Correct Answer: B

Instead add an SSH key to the node, and then you create an SSH connection.

References: https://docs.microsoft.com/en-us/azure/aks/ssh

Correct Answer: C

Bots in Microsoft Teams can be part of a one-to-one conversation, a group chat, or a channel in a Team.

Note: In Microsoft Teams, teams are groups of people brought together for work, projects, or common interests. Teams are made up of channels. Each channel is built around a topic, like "Team Events," a department name, or just for fun. Channels are where you hold meetings, have conversations, and work on files together.

References: https://docs.microsoft.com/en-us/microsoftteams/platform/bots/what-are-bots

Correct Answer: B

You can deploy LUIS on-premise as Docker Image in a container.

Note: Azure Cognitive LUIS service can be deployed on any hardware or on any host (Linus, Windows and IOS). This feature allows enterprises to quickly train the LUIS model on the cloud and deploy it anywhere which makes Cognitive services to be available truly to every person and every Organization - "Democratizing AI".

Reference: https://www.linkedin.com/pulse/deploying-microsoft-azure-cognitive-luis-service-on-premise-s

Correct Answer: B

The given solution does not accomplish the objective of minimizing custom code. While Integration Runtime can be used to move data from an on-premises server to Azure Storage, and Azure API Management can be used to consume

Cognitive Services APIs, it does not eliminate the need for custom code.

To minimize custom code and simplify the deployment of the pipeline, you should consider using Azure Logic Apps. Azure Logic Apps provide a serverless and code-free way to orchestrate workflows and integrate different systems and

services.

Reference:

https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime https://docs.microsoft.com/en-us/azure/logic-apps/logic-apps-examples-and-scenarios

Correct Answer: C

LargePersonGroup and LargeFaceList are collectively referred to as large-scale operations. LargePersonGroup can contain up to 1 million persons, each with a maximum of 248 faces. LargeFaceList can contain up to 1 million faces. The

large-scale operations are similar to the conventional PersonGroup and FaceList but have some differences because of the new architecture.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-scale

Correct Answer: B

With Azure-SSIS Integration Runtime you would need to write custom code Reference: https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime https://docs.microsoft.com/en-us/azure/logic-apps/logic-apps-examples-and-scenarios

Correct Answer: AD

A. Make use of the Face API: The Face API can be used to detect and identify individuals in images and videos. In this case, it can be utilized to identify each student in the virtual classroom for attendance purposes based on their facial features. This API can help capture the audio and video data of the students by recognizing their faces and linking them to their identities.

D. Make use of the Video Indexer API: The Video Indexer API enables the analysis and extraction of insights from video content. It can be employed to capture the audio and video data of the students in the virtual classroom. Additionally, the Video Indexer API offers capabilities for facial emotion recognition, which can help identify when a student's facial expression indicates difficulty. This can trigger an alert for the teacher, allowing timely intervention.

Correct Answer: EFG

Scenario: Data scientists must test Butler by using ASDK.

Note: Contoso wants to provide a new version of the Bookings app that will provide a highly available, reliable service for booking travel packages by interacting with a chatbot named Butler.

E: The ASDK (Azure Stack Development Kit) is meant to provide an environment in which you can evaluate Azure Stack and develop modern applications using APIs and tooling consistent with Azure in a non-production environment. Microsoft Azure Stack integrated systems range in size from 4-16 nodes, and are jointly supported by a hardware partner and Microsoft.

F: The Language Understanding (LUIS) container loads your trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints.

Use the docker pull command to download a container image from the mcr.microsoft.com/azure-cognitive-services/luis repository: docker pull mcr.microsoft.com/azure-cognitive-services/luis:latest

G: You can test using the endpoint with a maximum of two versions of your app. With your main or live version of your app set as the production endpoint, add a second version to the staging endpoint.

Reference: https://docs.microsoft.com/en-us/azure-stack/asdk/asdk-what-is https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-test