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Free Microsoft AI-100 Exam Dumps Questions & Answers
| Exam Code/Number: | AI-100Join the discussion |
| Exam Name: | Designing and Implementing an Azure AI Solution |
| Certification: | Microsoft |
| Question Number: | 163 |
| Publish Date: | Jul 19, 2026 |
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Total 163 questions
Your company has a data team of Scala and R experts.
You plan to ingest data from multiple Apache Kafka streams.
You need to recommend a processing technology to broker messages at scale from the Kafka streams to Azure Storage.
What should you recommend?
You plan to build an application that will perform predictive analytics. Users will be able to consume the application data by using Microsoft Power Bl or a custom website.
You need to ensure that you can audit application usage.
Which auditing solution should you use?
You create an image classification model in Azure Machine Learning Studio.
You need to deploy the model as a containerized web service.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Explanation

The following diagram illustrates the complete deployment workflow:

The deployment workflow includes the following steps:
* Register the model in a registry hosted in your Azure Machine Learning Service workspace
* Register an image that pairs a model with a scoring script and dependencies in a portable container
* Deploy the image as a web service in the cloud or to edge devices
* Monitor and collect data
* Update a deployment to use a new image.
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/service/concept-model-management-and-deploym
Von have an Azure SQL database w Azure Data Lake Storage Gen 2 account, and an API developed by using Azure Machine Learning Studio.
You need to ingest data once daily from the database, score each row by using the API, and write the data to the storage account.
Solution: You create a scheduled Jupyter Notebook in Azure Databricks.
Does this meet the goal?
You are developing a mobile application that will perform optical character recognition (OCR) from photos.
The application will annotate the photos by using metadata, store the photos in Azure Blob storage, and then score the photos by using an Azure Machine Learning model.
What should you use to process the data?