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Taking practice tests is particularly helpful for those who have exam anxiety. Our practice tests are user-friendly and customizable. Windows support the desktop practice test software. Our web-based practice test is compatible with all browsers and operating systems. The web-based Microsoft Azure AI Fundamentals (AI-900) practice test is similar to the desktop-based exam and can be taken on any browser without needing to download separate software.
| Section | Weight | Objectives |
|---|---|---|
| Features of generative AI workloads on Azure | 20–25% | - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts - Describe use cases for generative AI - Describe responsible AI practices for generative AI |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Computer Vision |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe considerations for developing AI solutions - Identify types of AI workloads - Describe responsible AI principles |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech - Describe capabilities of Azure Language |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe core concepts of machine learning - Describe machine learning pipelines |
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NEW QUESTION # 267
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:
These answers align with the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore conversational AI in Microsoft Azure."
1. A webchat bot can interact with users visiting a website # Yes
This statement is true. The Azure Bot Service allows developers to create intelligent chatbots that can be integrated into a webchat interface. This enables visitors to interact with the bot directly from a website, asking questions and receiving automated responses. This is a typical use case of conversational AI, where natural language processing (NLP) is used to interpret and respond to user input conversationally.
2. Automatically generating captions for pre-recorded videos is an example of conversational AI # No This statement is false. Automatically generating captions from video content is an example of speech-to-text (speech recognition) technology, not conversational AI. While it uses AI to convert spoken words into text, it lacks the two-way interactive communication characteristic of conversational AI. This task is typically handled by the Azure AI Speech service, which transcribes spoken content.
3. A smart device in the home that responds to questions such as "What will the weather be like today?" is an example of conversational AI # Yes This statement is true. Smart home assistants that engage in dialogue with users are powered by conversational AI. These devices use speech recognition to understand spoken input, natural language understanding (NLU) to determine intent, and speech synthesis (text-to-speech) to respond audibly. This represents the full conversational AI loop, where machines communicate naturally with humans.
NEW QUESTION # 268
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:
This question is derived from the Microsoft Azure AI Fundamentals (AI-900) learning module, particularly under "Describe features of conversational AI workloads on Azure." It tests understanding of chatbot capabilities and design principles within the context of Azure Bot Service and Conversational AI.
* Chatbots can support voice input - YesAccording to the AI-900 official materials, conversational AI systems such as chatbots can interact with users through text or voice. Using speech recognition services like Azure Cognitive Services Speech-to-Text, bots can interpret spoken input, and with Text- to-Speech, they can respond verbally. This enables voice-based chatbots used in virtual assistants, call centers, and customer support. Hence, voice input is fully supported by conversational AI solutions in Azure.
* A separate chatbot is required for each communication channel - NoThe Azure Bot Service is designed to provide multi-channel communication from a single bot instance. A single chatbot can communicate across several channels such as Microsoft Teams, Web Chat, Slack, Facebook Messenger, and email without needing separate bots for each platform. This centralized design allows developers to create, deploy, and manage one bot while configuring multiple channel connections through the Azure portal.
Therefore, the statement is false.
* Chatbots manage conversation flows by using a combination of natural language and constrained option responses - YesIn Microsoft's AI-900 training, chatbots are described as using Natural Language Processing (NLP) to understand free-form user input while also guiding interactions with predefined options such as buttons or quick replies. This hybrid approach ensures both flexibility and control, improving user experience and accuracy. Bots can interpret natural language via services like Language Understanding (LUIS) and also present structured options to guide conversations efficiently.
NEW QUESTION # 269
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:
Reference:
https://docs.microsoft.com/en-gb/azure/cognitive-services/text-analytics/overview
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-services/
https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure
NEW QUESTION # 270
You need to predict the animal population of an area.
Which Azure Machine Learning type should you use?
Answer: B
NEW QUESTION # 271
You need to identify harmful content in a generative Al solution that uses Azure OpenAI Service.
What should you use?
Answer: D
NEW QUESTION # 272
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