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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Extract text and handwriting from images - Build and deploy custom vision models - Analyze images and detect objects/features - Process and index video content |
| Topic 2: Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Understand agent use cases and types - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service |
| Topic 3: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers |
| Topic 4: Plan and manage an Azure AI solution | 20-25% | - Create and configure Azure AI resources - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Plan solutions aligned with responsible AI principles - Monitor, optimize, and secure AI solutions - Select suitable AI models - Select appropriate Microsoft Foundry Services |
| Topic 5: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Build knowledge bases and search indexes - Extract entities, relationships, and key phrases |
| Topic 6: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection |
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NEW QUESTION # 248
You are building an app by using the Speech SDK. The app will translate speech from French to German by using natural language processing.
You need to define the source language and the output language.
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:
SpeechRecognitionLanguage must be set to "fr" (French).
AddTargetLanguage("de") must be used to specify German as the translation output.
var speechTranslationConfig =
SpeechTranslationConfig.FromSubscription(speechKey, speechRegion);
speechTranslationConfig.SpeechRecognitionLanguage = "fr";
speechTranslationConfig.AddTargetLanguage("de");
* SpeechRecognitionLanguage # sets the source spoken language that the Speech service listens to (here, French).
* AddTargetLanguage("de") # adds German as the target translation language.
* SpeechSynthesisLanguage would be used if you want to speak out the translation, but since the requirement is only about defining input and output languages, we use AddTargetLanguage.
* Speech translation with Speech SDK
Final Answer:
* First blank # SpeechRecognitionLanguage
* Second blank # AddTargetLanguage
NEW QUESTION # 249
You are building a chatbot that will provide information to users as shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/microsoftteams/platform/task-modules-and-cards/cards/cards-reference
https://docs.microsoft.com/en-us/composer/how-to-send-cards?tabs=v1x
NEW QUESTION # 250
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a chatbot that uses question answering in Azure Cognitive Service for Language Users report that the responses of the chatbot lack formality when answering spurious questions You need to ensure that the chatbot provides formal responses to spurious questions.
Solution: From Language Studio, you change the chitchat source to qna_chitchat_professional.tsv. and then retrain and republish the model.
Does this meet the goal?
Answer: B
NEW QUESTION # 251
You are building a model that will be used in an iOS app.
You have images of cats and dogs. Each image contains either a cat or a dog.
You need to use the Custom Vision service to detect whether the images is of a cat or a dog.
How should you configure the project in the Custom Vision portal? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Classification
Box 2: Multiclass
A multiclass classification project is for classifying images into a set of tags, or target labels. An image can be assigned to one tag only.
Box 3: General
General: Optimized for a broad range of image classification tasks. If none of the other specific domains are appropriate, or if you ' re unsure of which domain to choose, select one of the General domains.
Reference:
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html
NEW QUESTION # 252
Hotspot Question
You have a bot that was built by using the Microsoft Bot Framework composer as shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
https://learn.microsoft.com/en-us/composer/concept-language-understanding?tabs=v2x#entities Entities are a collection of objects, each consisting of data extracted from an utterance such as places, times, and people. Entities and intents are both important data extracted from utterances.
An utterance may include zero or more entities, while an utterance usually represents one intent.
In Composer, all entities are defined and managed inline. Entities in the .lu file format are denoted using {\<entityName\>=\<labelled value\>} notation.
https://learn.microsoft.com/en-us/composer/concept-events-and-triggers?tabs=v2x#intent-triggers
NEW QUESTION # 253
......
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