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| Section | Weight | Objectives |
|---|---|---|
| Implement Generative AI Solutions | 10-15% | - Implement prompt engineering techniques - Apply responsible AI practices - Use Azure OpenAI Service for generative AI - Integrate Azure OpenAI models into applications |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Implement Azure AI Search solutions - Create custom skills for Azure AI Search - Implement semantic and vector search - Design document processing pipelines |
| Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Translate text and speech - Create conversational AI solutions with Azure AI Bot Service - Implement speech capabilities using Azure AI Speech - Analyze text using Azure AI Language |
| Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Plan and Manage an Azure AI Solution | 15-20% | - Plan and configure secure AI solutions - Implement governance and compliance for AI solutions - Manage AI costs and resource allocation - Select appropriate Azure AI services and technologies |
| Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Analyze images using Azure AI Vision - Implement object detection and image classification - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service |
>> New AI-102 Test Questions <<
Microsoft AI-102 practice test software contains many Microsoft AI-102 practice exam designs just like the real Designing and Implementing a Microsoft Azure AI Solution (AI-102) exam. These AI-102 practice exams contain all the AI-102 questions that clearly and completely elaborate on the difficulties and hurdles you will face in the final AI-102 Exam. We update our Microsoft AI-102 exam questions bank regularly to match the changes and improve the quality of AI-102 questions so you can get a better experience.
NEW QUESTION # 46
You are building a transcription service for technical podcasts.
Testing reveals that the service fails to transcribe technical terms accurately.
You need to improve the accuracy of the service.
Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation:
https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/custom-speech-overview#how-does-it- With Custom Speech, you can upload your own data, test and train a custom model, compare accuracy between models, and deploy a model to a custom endpoint.
- Create a project and choose a model. Use a Speech resource that you create in the Azure portal. If you will train a custom model with audio data, choose a Speech resource region with dedicated hardware for training audio data.
- Upload test data. Upload test data to evaluate the speech to text offering for your applications, tools, and products.
- Train a model. Provide written transcripts and related text, along with the corresponding audio data. Testing a model before and after training is optional but recommended.
- Deploy a model. Once you're satisfied with the test results, deploy the model to a custom endpoint. With the exception of batch transcription, you must deploy a custom endpoint to use a Custom Speech model.
NEW QUESTION # 47
You have an Azure subscription. The subscription contains an Azure OpenAI resource that hosts a GPT-3.5 Turbo model named Model1.
You configure Model1 to use the following system message: "You are an Al assistant that helps people solve mathematical puzzles. Explain your answers as if the request is by a 4-year-old." Which type of prompt engineering technique is this an example of?
Answer: C
NEW QUESTION # 48
You are building a chatbot for a Microsoft Teams channel by using the Microsoft Bot Framework SDK. The chatbot will use the following code.
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: Yes
The ActivityHandler.OnMembersAddedAsync method overrides this in a derived class to provide logic for when members other than the bot join the conversation, such as your bot's welcome logic.
Box 2: Yes
membersAdded is a list of all the members added to the conversation, as described by the conversation update activity.
Box 3: No
Reference:
https://docs.microsoft.com/en-us/dotnet/api/microsoft.bot.builder.activityhandler.onmembersaddedasync?view=b
NEW QUESTION # 49
You have a question answering project in Azure Cognitive Service for Language.
You need to move the project to a Language service instance in a different Azure region.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Comprehensive Detailed Explanation To move a Question Answering project to a different Azure region, you migrate the project data and then re-deploy it in the target region:
* Export the existing project (source region). In Language Studio (Question Answering), you first export the project. This produces a package (JSON/ZIP) containing your knowledge bases, sources, synonyms, and settings. Exporting is the supported way to move a project between resources/regions.
* Import the project into the new Language service instance (target region). In the target region's Language service instance, use Language Studio to import the previously exported file. This recreates the project (KBs and configuration) under the new resource.
* Train and publish from the new instance. After import, you must train (build) and then publish the project so that an endpoint is created under the new regional resource. Clients can then point to the new endpoint and key.
Actions like "enable custom text classification" or "regenerate the keys" are not required for moving a Question Answering project, and training/publishing from the original instance won't deploy to the target region.
Microsoft Azure AI Solution References
* Export and import Question Answering projects in Language Studio (move between resources/regions):
Microsoft Learn - Export and import projects (Question Answering) . https://learn.microsoft.com/azure
/ai-services/language-service/question-answering/how-to/export-import-project
* Train and publish a Question Answering project: Microsoft Learn - Create, train, and publish projects (Question Answering) . https://learn.microsoft.com/azure/ai-services/language-service/question- answering/how-to/create-test-deploy
* Language service overview and regional deployment concepts: Microsoft Learn - What is Azure AI Language? https://learn.microsoft.com/azure/ai-services/language-service/overview
NEW QUESTION # 50
You are developing a text processing solution.
You develop the following method.
You call the method by using the following code.
GetKeyPhrases(textAnalyticsClient, "the cat sat on the mat");
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: Yes
The Key Phrase Extraction API evaluates unstructured text, and for each JSON document, returns a list of key phrases.
Box 2: No
'the' is not a key phrase.
This capability is useful if you need to quickly identify the main points in a collection of documents. For example, given input text "The food was delicious and there were wonderful staff", the service returns the main talking points: "food" and "wonderful staff".
Box 3: No
Key phrase extraction does not have confidence levels.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-keyword-
NEW QUESTION # 51
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