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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe features of computer vision workloads on Azure | 15-20% | - Describe Azure capabilities for computer vision - Identify common computer vision tasks - Identify Azure AI services for computer vision |
| Topic 2: Describe AI workloads and considerations | 15-20% | - Identify guiding principles for responsible AI - Identify features of common AI workloads |
| Topic 3: Describe fundamental principles of machine learning on Azure | 30-35% | - Describe features of no-code automated ML - Describe Azure Machine Learning capabilities - Describe core machine learning concepts - Identify common machine learning tasks |
| Topic 4: Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe generative AI concepts - Describe Azure OpenAI Service capabilities |
| Topic 5: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Describe Azure capabilities for NLP - Identify common NLP tasks - Identify Azure AI services for NLP |
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NEW QUESTION # 55
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer
NEW QUESTION # 56
Capturing text from images is an example of which type of Al capability?
Answer: C
Explanation:
The correct answer is B. Optical character recognition (OCR).
OCR is a key capability within the Computer Vision and Document Intelligence services in Azure AI that enables systems to detect and extract printed or handwritten text from images and scanned documents.
When capturing text from images, OCR technology analyzes visual patterns (shapes of letters and numbers) and converts them into machine-readable text. For example, a photo of a receipt, street sign, or printed report can be processed to extract textual content programmatically.
* A (Text analysis): Applies to NLP tasks such as sentiment detection or key phrase extraction, not image processing.
* C (Image description): Generates captions describing the scene or objects in an image.
* D (Object detection): Identifies and locates objects but does not extract text.
NEW QUESTION # 57
You need to develop a chatbot for a website. The chatbot must answer users' questions based on the information in the following documents:
A product troubleshooting guide in a Microsoft Word document
A frequently asked questions (FAQ) list on a webpage
Which service should you use to process the documents?
Answer: B
NEW QUESTION # 58
What are three stages in a transformer model? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
Answer: C,D,E
NEW QUESTION # 59
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using QnA Maker? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,B,E
Explanation:
Automatic extraction
Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-types
NEW QUESTION # 60
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