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Microsoft AI-900 Practice Test Questions, Microsoft AI-900 Exam Practice Test Questions
The individuals who passed the Microsoft AI-900 exam possess the foundational knowledge of artificial intelligence (AI) and machine learning (ML). The test is designed to evaluate the candidates’ understanding of basic AI and ML workloads as well as how to execute them on Microsoft Azure. The students can earn the Microsoft Certified: Azure AI Fundamentals certification at the end of their journey with this path.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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Exam AI-900: Microsoft Azure AI Fundamentals
Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.
This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.
Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.
Part of the requirements for: Microsoft Certified: Azure AI Fundamentals
The Microsoft AI-900 exam, usually known as the Microsoft Azure AI Fundamentals, is well suited to baseline-level IT specialists with knowledge of artificial intelligence (AI) & Machine Learning (ML), and the relevant Microsoft Azure concepts. This is the only test that you should pass to qualify for the Microsoft Certified: Azure AI Fundamentals certification.
In case you're eager to get to know more about artificial intelligence facets & machine learning functions that relate to Microsoft Azure, then you're recommended to opt for AI-900 test.
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Microsoft AI-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Topic 2: Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Topic 3: Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|
| Topic 4: Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
Microsoft Azure AI Fundamentals Sample Questions:
Which AI service should you use to create a bot from a frequently asked questions (FAQ) document?
- A. Text Analytics
- B. QnA Maker
- C. Language Understanding (LUIS)
- D. Speech
Correct Answer: B 🗳️
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A company employs a team of customer service agents to provide telephone and email support to customers.
The company develops a webchat bot to provide automated answers to common customer queries.
Which business benefit should the company expect as a result of creating the webchat bot solution?
- A. a reduced workload for the customer service agents
- B. increased sales
- C. improved product reliability
Correct Answer: A 🗳️
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For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: No
Box 2: Yes
Box 3: Yes
Anomaly detection encompasses many important tasks in machine learning:
Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred.
Finding abnormal clusters of patients.
Checking values entered into a system.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection
Which three actions improve the quality of responses returned by a generative Al solution that uses GPT-3.5?
Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
- A. Add training data to prompts.
- B. Modify tokenization.
- C. Modify system messages.
- D. Provide additional examples to prompts.
- E. Add grounding data to prompts.
Correct Answer: C,D,E 🗳️
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For which two workloads can you use computer vision? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. assigning the color pixels in an image to object names
- B. creating visual representations of numerical data
- C. describing the contents of an image
- D. creating photorealistic images by using three-dimensional models
- E. detecting inconsistencies and anomalies in a stream of data
Correct Answer: A,C 🗳️
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