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| Section | Objectives |
|---|---|
| Topic 1: 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 |
| Topic 2: Implement Generative AI Solutions | - Integrate prompt engineering techniques - Implement Azure OpenAI Service solutions - Build retrieval-augmented generation (RAG) solutions |
| Topic 3: Implement Computer Vision Solutions | - Analyze images and videos using Azure AI Vision - Implement custom vision models - Extract information using OCR and form recognition |
| Topic 4: Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Manage security, compliance, and responsible AI - Select appropriate Azure AI services |
| Topic 5: Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
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NEW QUESTION # 306
You have a custom Azure OpenAI model.
You have the files shown in the following table.
You need to prepare training data for the model by using the OpenAI CLI data preparation tool. Which files can you upload to the tool?
Answer: A
Explanation:
You need to prepare training data for Azure OpenAI custom model fine-tuning using the OpenAI CLI data preparation tool .
Supported input formats: JSONL (primary).
CLI pre-processing accepted formats: TSV, CSV, JSON.
Not supported: PDF, XML, XLSX directly.
Checking files:
File1.tsv (80 MB) # Supported (CLI can convert TSV to JSONL).
File2.xml (25 MB) # Not supported (XML not accepted).
File3.pdf (50 MB) # Not supported.
File4.xlsx (200 MB) # Not supported directly.
NEW QUESTION # 307
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.
* 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.
The answer: 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
NEW QUESTION # 308
Your company has a repotting solution that has paginated reports. The reports query a dimensional model in a data warehouse. Which type of processing does the reporting solution use?
Answer: D
Explanation:
* Dimensional models and data warehouses are designed for OLAP workloads (aggregations, analytics, reporting).
* OLTP is for transaction-based line-of-business applications.
* Batch processing is about moving and transforming data, not querying.
* Stream processing handles continuous real-time data, not historical warehouse queries.
Reference: OLTP vs OLAP in Azure
NEW QUESTION # 309
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
Explanation:
* The chatbot uses Question Answering in Azure Cognitive Service for Language.
* Users report that the chatbot's responses to spurious questions (such as jokes, casual chitchat, or off- topic queries) are not formal enough.
In Question Answering projects, you can add chitchat sources provided by Microsoft to handle small talk.
These sources include:
* qna_chitchat_friendly.tsv # Informal/friendly responses.
* qna_chitchat_professional.tsv # Formal/professional responses.
* qna_chitchat_witty.tsv # Humorous/witty responses.
By changing the chitchat source to qna_chitchat_professional.tsv, then retraining and republishing, the bot will provide formal responses to spurious questions.
Therefore, this solution meets the goal.
The answer: A. Yes
* Add chit-chat to a Question Answering project
* Chit-chat personality types (friendly, professional, witty)
NEW QUESTION # 310
You are developing a method that uses the Computer Vision client library. The method will perform optical character recognition (OCR) in images. The method has the following code.
During testing, you discover that the call to the GetReadResultAsync method occurs before the read operation is complete.
You need to prevent the GetReadResultAsync method from proceeding until the read operation is complete.
Which two actions should you perform? Each correct answer presents part of the solution. (Choose two.) NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
Example code :
do
{
results = await client.GetReadResultAsync(Guid.Parse(operationId));
}
while ((results.Status == OperationStatusCodes.Running ||
results.Status == OperationStatusCodes.NotStarted));
Reference:
https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/ComputerVision/Comp
NEW QUESTION # 311
......
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