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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers |
| Topic 2: Plan and manage an Azure AI solution | 20-25% | - Create and configure Azure AI resources - Select suitable AI models - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services |
| Topic 3: Implement computer vision solutions | 10-15% | - Build and deploy custom vision models - Integrate vision capabilities into applications - Extract text and handwriting from images - Process and index video content - Analyze images and detect objects/features |
| Topic 4: Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Customize and deploy NLP models - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection |
| Topic 5: Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration - Understand agent use cases and types - Build agents with Microsoft Foundry Agent Service |
| Topic 6: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval - Build knowledge bases and search indexes |
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NEW QUESTION # 118
Match the Azure Cosmos DB APIs to the appropriate data structures.
To answer, drag the appropriate API from the column on the left to its data structure on the right. Each API may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
NEW QUESTION # 119
You are building a chatbot for a travel agent. The chatbot will use the Azure OpenAI GPT 3.5 model and will be used to make travel reservations.
You need to maximize the accuracy of the responses from the chatbot.
What should you do?
Answer: A
NEW QUESTION # 120
You are building a customer support chatbot.
You need to configure the bot to identify the following:
* Code names for internal product development
* Messages that include credit card numbers
The solution must minimize development effort.
Which Azure Cognitive Service for Language feature should you use for each requirement? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The chatbot needs to recognize two different kinds of information:
* Code names for internal product development
* These are not standard entities like "locations" or "organizations" that prebuilt NER can detect.
* You need to train a custom model to recognize internal terms or codenames (for example,
"Project Falcon").
* The correct Azure Cognitive Service for Language feature is Custom Named Entity Recognition (Custom NER), which allows defining and training entity categories specific to your business.
* Messages that include credit card numbers
* Credit card numbers are sensitive data falling under Personally Identifiable Information (PII).
* Azure Cognitive Service for Language provides a PII detection feature that automatically identifies and masks sensitive information such as credit card numbers, SSNs, and phone numbers.
* This minimizes development effort since it is prebuilt and ready to use.
Correct Answer Mapping:
* Identify code names for internal product development # Custom named entity recognition (NER)
* Identify messages that include credit card numbers # Personally Identifiable Information (PII) detection
* Custom Named Entity Recognition in Azure AI Language
* PII detection in Azure AI Language
Microsoft References
NEW QUESTION # 121
You have a Computer Vision resource named contoso1 that is hosted in the West US Azure region.
You need to use contoso1 to make a different size of a product photo by using the smart cropping feature.
How should you complete the API URL? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 122
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:
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 # 123
......
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