Microsoft AI-900 Microsoft Azure AI Fundamentals Online Training
Microsoft AI-900 Online Training
The questions for AI-900 were last updated at Nov 23,2024.
- Exam Code: AI-900
- Exam Name: Microsoft Azure AI Fundamentals
- Certification Provider: Microsoft
- Latest update: Nov 23,2024
Which AI service can you use to interpret the meaning of a user input such as “Call me back later?”
- A . Translator Text
- B . Text Analytics
- C . Speech
- D . Language Understanding (LUIS)
You use natural language processing to process text from a Microsoft news story.
You receive the output shown in the following exhibit.
Which type of natural languages processing was performed?
- A . entity recognition
- B . key phrase extraction
- C . sentiment analysis
- D . translation
You are developing a natural language processing solution in Azure. The solution will analyze customer reviews and determine how positive or negative each review is.
This is an example of which type of natural language processing workload?
- A . language detection
- B . sentiment analysis
- C . key phrase extraction
- D . entity recognition
You build a QnA Maker bot by using a frequently asked questions (FAQ) page.
You need to add professional greetings and other responses to make the bot more user friendly.
What should you do?
- A . Increase the confidence threshold of responses
- B . Enable active learning
- C . Create multi-turn questions
- D . Add chit-chat
You are building a Language Understanding model for an e-commerce business.
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?
- A . Test the model by using new utterances
- B . Add utterances to the None intent
- C . Create a prebuilt task entity
- D . Create a new model
DRAG DROP
Match the types of natural languages processing workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point.
HOTSPOT
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
DRAG DROP
You plan to apply Text Analytics API features to a technical support ticketing system.
Match the Text Analytics API features to the appropriate natural language processing scenarios.
To answer, drag the appropriate feature from the column on the left to its scenario on the right. Each feature may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point.
You are developing a solution that uses the Text Analytics service.
You need to identify the main talking points in a collection of documents.
Which type of natural language processing should you use?
- A . entity recognition
- B . key phrase extraction
- C . sentiment analysis
- D . language detection
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