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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots - Implement translation and summarization |
| Topic 2: Plan and manage an Azure AI solution | 20-25% | - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Select suitable AI models - Plan solutions aligned with responsible AI principles - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services |
| Topic 3: Implement an agentic solution | 5-10% | - Understand agent use cases and types - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service |
| Topic 4: Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models |
| Topic 5: Implement computer vision solutions | 10-15% | - Process and index video content - Analyze images and detect objects/features - Integrate vision capabilities into applications - Build and deploy custom vision models - Extract text and handwriting from images |
| Topic 6: Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases |
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NEW QUESTION # 12
You have an Azure subscription that contains an Azure Al Content Safety resource named CS1.
You need to call CS1 to identify whether a user request contains hateful language.
How should you complete the command? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point
Answer:
Explanation:
Explanation:
NEW QUESTION # 13
You are developing the shopping on-the-go project.
You are configuring access to the QnA Maker resources.
Which role should you assign to AllUsers and LeadershipTeam? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: QnA Maker Editor
Scenario: Provide all employees with the ability to edit Q&As.
The QnA Maker Editor (read/write) has the following permissions:
Create KB API
Update KB API
Replace KB API
Replace Alterations
"Train API" [in
new service model v5]
Box 2: Contributor
Scenario: Only senior managers must be able to publish updates.
Contributor permission: All except ability to add new members to roles
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/reference-role-based-access-control
NEW QUESTION # 14
You have 100,000 images.
You need to build an app that will perform the following actions:
* Identify road signs in the images and generate a short description of each road sign.
* Analyze the descriptions to generate a report about the different types of road signs and how often each type occurred.
The solution must minimize costs.
What should you use for each action? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Explanation:
Identify the road signs and generate a short description of each road sign: Azure AI Vision is the most suitable choice for this task. It is designed for image analysis and can accurately detect and describe objects such as road signs in large datasets like your 100,000 images. This service is optimized for computer vision tasks and helps minimize costs by efficiently processing images at scale.
Analyze the descriptions to generate a report about the different types of road signs and how often each type occurred: Azure OpenAI GPT-4-Turbo is ideal for this action. It can process natural language descriptions, identify patterns, and generate a detailed report based on the frequency of different road sign types. This model is cost-effective for text analysis tasks and can handle the volume of data derived from the image descriptions while providing advanced language understanding.
NEW QUESTION # 15
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation
NEW QUESTION # 16
You are developing the knowledgebase by using Azure Cognitive Search.
You need to meet the knowledgebase requirements for searching equivalent terms.
What should you include in the solution?
Answer: B
Explanation:
Within a search service, synonym maps are a global resource that associate equivalent terms, expanding the scope of a query without the user having to actually provide the term. For example, assuming "dog", "canine", and "puppy" are mapped synonyms, a query on "canine" will match on a document containing "dog".
Create synonyms: A synonym map is an asset that can be created once and used by many indexes.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-synonyms
NEW QUESTION # 17
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