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One of the key objectives of the Microsoft AI-102 Exam is to test candidates' ability to design and implement machine learning models using Azure Machine Learning. This includes understanding how to select appropriate algorithms, prepare data for training, and fine-tune models to achieve the best possible performance. Candidates will also be tested on their ability to deploy machine learning models as web services using Azure Kubernetes Service (AKS).
Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.
This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.
It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.
After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.
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To prepare for the Microsoft AI-102 exam, candidates should have a strong understanding of Azure services and AI concepts. They should also have experience in designing and implementing AI solutions, as well as knowledge of programming languages such as Python and C#. In addition, candidates should be familiar with machine learning concepts such as supervised and unsupervised learning, deep learning, and reinforcement learning. With the Microsoft AI-102 Certification, professionals can demonstrate their expertise in AI solution development and implementation on the Azure platform, opening up opportunities for career advancement and higher salaries.
NEW QUESTION # 190
You have an app that uses the AI Language custom question answering service.
You need to ad alternatives for the word testing by using the Authoring API.
How should you complete the JSON payload? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* In Custom Question Answering (part of Azure AI Language), if you want to define alternative words or spellings for a specific term (e.g., testing, trials, evaluate), you must use the alterations property.
* Each alteration object contains a list of alternative values for the same meaning.
* Example:
* {
* "alterations": [
* {
* "alterations": [
* "testing",
* "trials",
* "evaluate"
* ]
* }
* ]
* }
* phrases is used for pattern matching in question-answer pairs.
* synonyms is used for synonyms within LUIS (Language Understanding), not for QnA alterations.
* value is used inside synonyms definitions in some contexts but not here.
The JSON should be:
{
"alterations": [
{
"alterations": [
"testing",
"trials",
"evaluate"
]
}
]
}
Verified Answer:
* Left box: "alterations"
* Right box: "alterations"
Microsoft References:
* Manage alterations in Custom Question Answering (Azure AI Language)
* Authoring API reference for alterations
NEW QUESTION # 191
You need to create a visualization of running sales totals per quarter as shown in the following exhibit.
What should you create in Cower Bl Desktop;1
Answer: B
NEW QUESTION # 192
Hotspot Question
You have an Azure subscription that contains an Azure AI Content Safety resource named resource1.
You are building an app that will analyze text by using resource1.
You need to identify text that contains hateful content.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
"categories_analysis"
The categories_analysis property contains categorized insights into the type of content detected in the text, including hate speech.
blocklist_match would be used if the system were matching against a predefined blocklist, which is not the case here.
content is too broad and does not specifically analyze the detected category.
"{hate_result.severity}"
severity represents the intensity or degree of hateful content detected in the text.
This is the most relevant choice to quantify and report the level of hate detected.
Other options like blocklist_item_id or blocklist_item_text are only applicable when matching against blocklists.
NEW QUESTION # 193
Case Study 2 - Contoso, Ltd.
General Overview
Contoso, Ltd. is an international accounting company that has offices in France. Portugal, and the United Kingdom. Contoso has a professional services department that contains the roles shown in the following table.
Infrastructure
Contoso has the following subscriptions:
- Azure
- Microsoft 365
- Microsoft Dynamics 365
Azure Active (Azure AD) Directory
Contoso has Azure Active Directory groups for securing role-based access. The company uses the following group naming conventions:
- ICountryJ-[Levell-[Role]
- [Level]-[Role]
Intellectual Property
Contoso has the intellectual property shown in the following table.
Text-based content is provided only in one language and is not translated.
Planned Projects
Contoso plans to develop the following:
- A document processing workflow to extract information automatically from PDFs and images of financial documents
- A customer-support chatbot that will answer questions by using FAQs
- A searchable knowledgebase of all the intellectual property
Technical Requirements
Contoso identifies the following technical requirements:
- All content must be approved before being published.
- All planned projects must support English, French, and Portuguese.
- All content must be secured by using role-based access control (RBAC).
- RBAC role assignments must use the principle of least privilege.
- RBAC roles must be assigned only to Azure Active Directory groups.
- Al solution responses must have a confidence score that is equal to or greater than 70 percent.
- When the response confidence score of an Al response is lower than 70 percent, the response must be improved by human input.
Chatbot Requirements
Contoso identifies the following requirements for the chatbot:
- Provide customers with answers to the FAQs.
- Ensure that the customers can chat to a customer service agent.
- Ensure that the members of a group named Management-Accountants can approve the FAQs.
- Ensure that the members of a group named Consultant-Accountants can create and amend the FAQs.
- Ensure that the members of a group named the Agent-CustomerServices can browse the FAQs.
- Ensure that access to the customer service agents is managed by using Omnichannel for Customer Service.
- When the response confidence score is low.
- Ensure that the chatbot can provide other response options to the customers.
Document Processing Requirements
Contoso identifies the following requirements for document processing:
- The document processing solution must be able to process standardized financial documents that have the following characteristics:
- Contain fewer than 20 pages.
- Be formatted as PDF or JPEG files.
- Have a distinct standard for each office.
- The document processing solution must be able to extract tables and text from the financial documents.
- The document processing solution must be able to extract information from receipt images.
- Members of a group named Management-Bookkeeper must define how to extract tables from the financial documents.
- Members of a group named Consultant-Bookkeeper must be able to process the financial documents.
Knowledgebase Requirements
Contoso identifies the following requirements for the knowledgebase:
- Supports searches for equivalent terms
- Can transcribe jargon with high accuracy
- Can search content in different formats, including video
- Provides relevant links to external resources for further research
You are developing the knowledgebase.
You use Azure Video Analyzer for Media (previously Video indexer) to obtain transcripts of webinars.
You need to ensure that the solution meets the knowledgebase requirements.
What should you do?
Answer: B
Explanation:
--- Can transcribe jargon with high accuracy
Video Indexer (VI), the AI service for Azure Media Services enables the customization of language models by allowing customers to upload examples of sentences or words belonging to the vocabulary of their specific use case. Since speech recognition can sometimes be tricky, VI enables you to train and adapt the models for your specific domain. Harnessing this capability allows organizations to improve the accuracy of the Video Indexer generated transcriptions in their accounts.
Reference:
https://azure.microsoft.com/en-us/blog/new-ways-to-train-custom-language-models-effortlessly/
NEW QUESTION # 194
You successfully run the following HTTP request.
POST https://management.azure.com/subscriptions/18c51a87-3a69-47a8-aedc-a54745f708a1/resourceGroups/RG1/providers/Microsoft.CognitiveServices/accounts/contosol/regenerateKey?api-version=2017-04-18 Body{"keyName": "Key2"} What is the result of the request?
Answer: A
Explanation:
https://docs.microsoft.com/en-us/rest/api/searchmanagement/2021-04-01-preview/query-keys/create
NEW QUESTION # 195
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