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| Section | Objectives |
|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | - Select appropriate Azure AI services - Manage security, compliance, and responsible AI - Plan solution requirements and architecture |
| Topic 2: Implement Knowledge Mining and Document Intelligence | - Enrich and index data for search scenarios - Implement document intelligence solutions - Build Azure AI Search solutions |
| Topic 3: Implement Computer Vision Solutions | - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision - Implement custom vision models |
| Topic 4: Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Topic 5: Implement Natural Language Processing Solutions | - Analyze text using Azure AI Language - Translate and interpret language using Azure AI services - Implement question answering and conversational AI |
>> Latest AI-102 Test Objectives <<
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NEW QUESTION # 48
You plan to build an agent that will combine and process multiple files uploaded by users.
You are evaluating whether to use the Azure AI Agent Service to develop the agent.
What is the maximum size of all the files that can be uploaded to the service?
Answer: C
Explanation:
https://learn.microsoft.com/en-us/azure/ai-services/agents/quotas-limits
NEW QUESTION # 49
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:
NEW QUESTION # 50
You are building an app that will process incoming email and direct email messages to either French or English language support teams.
Which Azure Cognitive Services API should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 51
You need to upload speech samples to a Speech Studio project. How should you upload the samples?
Answer: D
Explanation:
When working with Speech Studio in Azure AI Speech (for example, to build a custom speech model for recognition or training purposes), you must provide speech samples along with their transcripts.
* Audio File Format
* The supported format is .wav (PCM, 16-bit, 16 kHz or 8 kHz mono).
* Other formats like .wma, .flac, or .mp3 are not accepted for training custom models.
* Batch Upload via .zip
* Audio files must be placed in a .zip archive.
* The .zip file must also include a transcription file (usually a .txt or .json file) that maps the spoken audio in each .wav file to the correct text.
* Transcript Format
* Transcripts must be plain text, not Microsoft Word documents.
* The transcript must align correctly with each audio file to ensure the Speech service learns from accurate mappings.
Requirements for Uploading Speech Samples:
* A. Combine into one .wma file
* Incorrect. .wma is not supported. Also, Speech Studio expects multiple .wav samples, not one big file.
* B. Upload a .zip file containing .wav files + transcript
* Correct. This is the officially supported method for uploading training data into a Speech Studio project.
* C. Upload .flac files with Word transcript
* Incorrect. .flac is not supported. Transcripts must be plain text, not Word files.
* D. Upload individual .wma files
* Incorrect. .wma is not supported.
Option Analysis
B). Upload a .zip file that contains a collection of audio files in the .wav format and a corresponding text transcript file.
* Prepare training data for Custom Speech
* Speech Studio - Data Requirements
Microsoft References
NEW QUESTION # 52
You have an Azure OpenAI model.
You have 500 prompt-completion pairs that will be used as training data to fine-tune the model.
You need to prepare the training data.
Which format should you use for the training data file?
Answer: B
Explanation:
For Azure OpenAI fine-tuning, training data must be provided as a JSON Lines (.jsonl) file. Each line represents one example. Because your data is described as prompt-completion pairs, the required shape is typically:
{"prompt": "<your prompt>", "completion": "<ideal completion>"}
(Chat model fine-tuning instead uses a messages array per line, but the file format is still JSONL.) JSONL is the only accepted format for upload to the fine-tuning job.
Microsoft References
* Azure OpenAI Service - Fine-tuning: data preparation and formats (JSONL; prompt-completion and chat messages).
* Azure OpenAI Service - How to fine-tune models (training files must be .jsonl).
NEW QUESTION # 53
......
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