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Microsoft AI-102 Exam Syllabus Topics:

SectionObjectives
Implement Generative AI Solutions- Implement Azure OpenAI Service solutions
- Build retrieval-augmented generation (RAG) solutions
- Integrate prompt engineering techniques
Implement Computer Vision Solutions- Extract information using OCR and form recognition
- Implement custom vision models
- Analyze images and videos using Azure AI Vision
Plan and Manage an Azure AI Solution- Plan solution requirements and architecture
- Manage security, compliance, and responsible AI
- Select appropriate Azure AI services
Implement Knowledge Mining and Document Intelligence- Build Azure AI Search solutions
- Implement document intelligence solutions
- Enrich and index data for search scenarios
Implement Natural Language Processing Solutions- Translate and interpret language using Azure AI services
- Analyze text using Azure AI Language
- Implement question answering and conversational AI

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q90-Q95):

NEW QUESTION # 90
You are building a chatbot by using the Microsoft Bot Framework Composer.
You have the dialog design shown in the following exhibit.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: No
User.name is a property.
Box 2: Yes
Box 3: Yes
The coalesce() function evaluates a list of expressions and returns the first non-null (or non-empty for string) expression.
Reference:
https://docs.microsoft.com/en-us/composer/concept-language-generation
https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/coalescefunction


NEW QUESTION # 91
You have an Azure subscription that contains an Azure Al Content Safety resource named CS1. You plan to build an app that will analyze user-gene rated documents and identify obscure offensive terms. You need to create a dictionary that will contain the offensive terms. The solution must minimize development effort.
What should you use?

Answer: A

Explanation:
Azure AI Content Safety supports custom blocklists -dictionaries of terms/phrases you define to detect obscure or domain-specific offensive terms in user content. Creating a blocklist is the minimal-effort, built- in way to meet this requirement; you don't need to build a classifier.
References
* Create and use blocklists in Azure AI Content Safety. https://learn.microsoft.com/azure/ai-services
/content-safety/concepts/blocklists
* Text moderation overview (using built-in classifiers with optional blocklists). https://learn.microsoft.
com/azure/ai-services/content-safety/concepts/text-moderation


NEW QUESTION # 92
You are building a chatbot by using the Microsoft Bot Framework SDK.
You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.
You create the following state accessors to store both objects in state.
var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile)); var conversationStateAccessors = _conversationState.CreateProperty<ConversationData>(nameof(ConversationData)); The state storage mechanism is set to Memory Storage.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-v4-state


NEW QUESTION # 93
You are developing a streaming Speech to Text solution that will use the Speech SDK and MP3 encoding.
You need to develop a method to convert speech to text for streaming MP3 data.
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:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-use-codec-compressed-audio-input-streams?tabs=debian&pivots=programming-language-csharp


NEW QUESTION # 94
You are building a chatbot that will use question answering in Azure Cognitive Service for Language.
You have a PDF named Docl.pdf that contains a product catalogue and a price list You upload Docl.pdf and train the model.
During testing, users report that the chatbot responds correctly to the following question: What is the price of < product>?
The chatbot fails to respond to the following question: How much does <product* cost?
You need to ensure that the chatbot responds correctly to both questions.
Solution: From Language Studio, you create an entity for cost, and then retrain and republish the model.
Does this meet the goal?

Answer: A


NEW QUESTION # 95
......

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