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                     Microsoft AI-100 Dumps PDF
Designing and Implementing an Azure AI Solution
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Question: 1 
   
You deploy an application that performs sentiment analysis on the data stored in Azure Cosmos DB. 
Recently, you loaded a large amount of data to the database. The data was for a customer named 
Contoso. Ltd. 
You discover that queries for the Contoso data are slow to complete, and the queries slow the entire 
application. 
You need to reduce the amount of time it takes for the queries to complete. The solution must 
minimize costs. 
What is the best way to achieve the goal? More than one answer choice may achieve the goal. Select 
the BEST answer. 
 
A. Change the requests units. 
B. Change the partitioning strategy. 
C. Change the transaction isolation level. 
D. Migrate the data to the Cosmos DB database. 
 
Answer: B         
 
Explanation: 
References: 
https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning 
 
Question: 2 
   
You have an Al application that uses keys in Azure Key Vault. 
Recently, a key used by the application was deleted accidentally and was unrecoverable. You need to 
ensure that if a key is deleted, it is retained in the key vault for 90 days. Which two features should 
you configure? Each correct answer presents part of the solution. NOTE: Each correct selection is 
worth one point 
 
A. the expiration date on the keys 
B. soft delete 
C. purge protection 
D. auditors 
E. the activation date on the keys 
 
Answer: BC     
 
Explanation: 
References: 
https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning 
 
 
Question: 3 
   
DRAG DROP 
You are designing an AI solution that will analyze media data. The data will be stored in Azure Blob 
storage. 
You need to ensure that the storage account is encrypted by using a key generated by the hardware 
security module (HSM) of your company. 
Which three 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. 
 
 
Answer:     
 
 
 
Explanation: 
References: 
 
https://docs.microsoft.com/en-us/azure/storage/common/storage-encryption-keys-portal 
https://docs.microsoft.com/en-us/azure/key-vault/key-vault-hsm-protected-keys 
 
Question: 4 
   
You deploy an Azure bot. 
You need to collect Key Performance Indicator (KPI) data from the bot. The type of data includes: 
• The number of users interacting with the bot 
• The number of messages interacting with the bot 
• The number of messages on different channels received by the bot 
• The number of users and messages continuously interacting with the bot 
What should you configure? 
 
A. Bot analytics 
B. Azure Monitor 
C. Azure Analysis Services 
D. Azure Application Insights 
 
Answer: A     
 
Explanation: 
References: 
https://docs.microsoft.com/en-us/azure/sql-database/saas-multitenantdb-adhoc-reporting 
 
Question: 5 
   
You need to configure versioning and logging for Azure Machine Learning models. Which Machine 
Learning service application should you use? 
 
A. models 
B. activities 
C. experiments 
D. pipelines 
E. deployments 
 
Answer: E     
 
Explanation: 
References: 
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-logging#loggingfor- 
deployed-models 
 
 
Question: 6 
   
Your company develops an AI application that is orchestrated by using Kubernetes. You need to 
deploy the application. 
Which three actions should you perform? Each correct answer presents part of the solution. NOTE: 
Each correct selection is worth one point. 
 
A. Create a Kubernetes cluster. 
B. Create an Azure Container Registry instance. 
C. Create a container image file. 
D. Create a Web App for Containers. 
E. Create an Azure container instance. 
 
Answer: ABC     
 
Explanation: 
References: 
https://docs.microsoft.com/en-us/azure/aks/tutorial-kubernetes-prepare-app 
 
Question: 7 
   
DRAG DROP 
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. 
 
 
Answer:  
 
 
 
 
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-modelmanagement- 
and-deployment#step-3-deploy-image 
 
Question: 8 
 
You create an Azure Machine Learning Studio experiment. 
You plan to publish the experiment as a Machine Learning Web service. 
You need to ensure that you can consume the web service from Microsoft Excel spreadsheets. 
What should you use? 
 
 
A. a Batch Execution Service (BES) and an Azure managed identity 
B. a Request-Response Service (RRS) and an Azure managed identity 
C. a Request-Response Service (RRS) and an API key 
D. a Batch Execution Service (BES) and an API key 
 
Answer: C     
 
Explanation: 
Steps to Add a New web service 
1. Deploy a web service or use an existing Web service. 
2. Click Consume. 
3. Look for the Basic consumption info section. Copy and save the Primary Key and the Request- 
Response 
URL. 
4. In Excel, go to the Web Services section (if you are in the Predict section, click the back arrow to go 
to the 
list of web services). 
5. Click Add Web Service. 
6. Paste the URL into the Excel add-in text box labeled URL. 
7. Paste the API/Primary key into the text box labeled API key. 
8. Click Add. 
References: 
https://docs.microsoft.com/en-us/azure/machine-learning/studio/excel-add-in-for-web-services 
 
Question: 9 
   
You plan to implement a new data warehouse for a planned AI solution. You have the following 
information regarding the data warehouse: 
•The data files will be available in one week. 
•Most queries that will be executed against the data warehouse will be ad-hoc queries. 
•The schemas of data files that will be loaded to the data warehouse will change often. 
•One month after the planned implementation, the data warehouse will contain 15 TB of data. 
You need to recommend a database solution to support the planned implementation. 
What two solutions should you include in the recommendation? Each correct answer is a complete 
solution. 
NOTE: Each correct selection is worth one point. 
 
A. Apache Hadoop 
B. Apache Spark 
C. a Microsoft Azure SQL database 
D. an Azure virtual machine that runs Microsoft SQL Server 
 
Answer: AB     
 
 
Question: 10 
   
DRAG DROP 
You need to build an A) solution that will be shared between several developers and customers. 
You plan to write code, host code, and document the runtime all within a single user experience. 
You build the environment to host the solution. 
Which three actions should you perform in sequence next? To answer, move the appropriate actions 
from the list of actions to the answer area and arrange them in the correct order. 
 
 
Answer:  
 
 
 
Explanation: 
Step 1: Create an Azure Machine Learning Studio workspace 
Step 2: Create a notebook 
You can manage notebooks using the UI, the CLI, and by invoking the Workspace API. 
To create a notebook 
Click the Workspace button Workspace Icon or the Home button Home Icon in the sidebar. Do one of 
the following: 
Next to any folder, click the Menu Dropdown on the right side of the text and select Create > 
Notebook. Create Notebook 
In the Workspace or a user folder, click Down Caret and select Create > Notebook. 
2. In the Create Notebook dialog, enter a name and select the notebook’s primary language. 
3. If there are running clusters, the Cluster drop-down displays. Select the cluster to attach the 
notebook to. 
 
4. Click Create. 
Step 3: Create a new experiment 
Create a new experiment by clicking +NEW at the bottom of the Machine Learning Studio window. 
Select EXPERIMENT > Blank Experiment. 
References: 
https://docs.azuredatabricks.net/user-guide/notebooks/notebook-manage.html 
https://docs.microsoft.com/en-us/azure/machine-learning/service/quickstart-run-cloud-notebook 
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