File Info
| Exam | Designing and Implementing an Azure AI Solution |
| Number | AI-100 |
| File Name | Microsoft.AI-100.PracticeTest.2019-04-16.25q.tqb |
| Size | 313 KB |
| Posted | Apr 16, 2019 |
| Download | Microsoft.AI-100.PracticeTest.2019-04-16.25q.tqb |
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Demo Questions
Question 1
You have an Azure Machine Learning model that is deployed to a web service.
You plan to publish the web service by using the name ml.contoso.com.
You need to recommend a solution to ensure that access to the web service is encrypted.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- Generate a shared access signature (SAS)
- Obtain an SSL certificate
- Add a deployment slot
- Update the web service
- Update DNS
- Create an Azure Key Vault
Correct answer: BDE
Explanation:
The process of securing a new web service or an existing one is as follows:Get a domain name. Get a digital certificate. Deploy or update the web service with the SSL setting enabled. Update your DNS to point to the web service. Note: To deploy (or re-deploy) the service with SSL enabled, set the ssl_enabled parameter to True, wherever applicable. Set the ssl_certificate parameter to the value of the certificate file and the ssl_key to the value of the key file. References:https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-secure-web-service The process of securing a new web service or an existing one is as follows:
- Get a domain name.
- Get a digital certificate.
- Deploy or update the web service with the SSL setting enabled.
- Update your DNS to point to the web service.
Note: To deploy (or re-deploy) the service with SSL enabled, set the ssl_enabled parameter to True, wherever applicable. Set the ssl_certificate parameter to the value of the certificate file and the ssl_key to the value of the key file.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-secure-web-service
Question 2
Your company recently deployed several hardware devices that contain sensors.
The sensors generate new data on an hourly basis. The data generated is stored on-premises and retained for several years.
During the past two months, the sensors generated 300 GB of data.
You plan to move the data to Azure and then perform advanced analytics on the data.
You need to recommend an Azure storage solution for the data.
Which storage solution should you recommend?
- Azure Queue storage
- Azure Cosmos DB
- Azure Blob storage
- Azure SQL Database
Correct answer: C
Explanation:
References:https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage
Question 3
You plan to design an application that will use data from Azure Data Lake and perform sentiment analysis by using Azure Machine Learning algorithms.
The developers of the application use a mix of Windows- and Linux-based environments. The developers contribute to shared GitHub repositories.
You need all the developers to use the same tool to develop the application.
What is the best tool to use? More than one answer choice may achieve the goal.
- Microsoft Visual Studio Code
- Azure Notebooks
- Azure Machine Learning Studio
- Microsoft Visual Studio
Correct answer: C
Explanation:
References:https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/studio/algorithm-choice.md References:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/studio/algorithm-choice.md
