Microsoft Azure AI Fundamentals Demo Questions
Here you can find Microsoft Azure AI Fundamentals exam sample questions which will help you to prepare for your upcoming certification test. These questions will give you an idea of what to expect on the exam and help you review the AI-900 study material. Be sure to go over the Free AI-900 questions multiple times so that you are confident and comfortable with the material. You can always go to the full AI-900 dumps here.
These Microsoft Azure AI Fundamentals certification questions are designed to give you a feel for the material you'll be tested on. They cover a wide range of topics, so you can get a sense of what to expect on examination day.
These AI-900 dumps are updated regularly, so you can be confident that you're studying with the most up-to-date information available. We also provide answer keys so that students can check their work.
Additionally, going through Microsoft Azure AI Fundamentals practice questions can help you identify any areas where you need more review. Taking advantage of our AI-900 demo questions is a great way to set yourself up for success on the real thing.
These Microsoft Azure AI Fundamentals questions cover the material that will be on the test, and provide an opportunity for students to practice their skills. The questions are designed to be similar to those that will be on the actual Microsoft Azure AI Fundamentals exam, so that students can get a feel for what they will be facing. We believe that by providing these demo questions, students will be better prepared and more likely to succeed on their exams.
Good luck for the AI-900 exam!
Microsoft Azure AI Fundamentals Sample Questions:
1. You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet the following requirements: Include one or more faces. Contain at least one person wearing sunglasses. What should you use to analyze the images?
A. the Verify operation in the Face service
B. the Detect operation in the Face service
C. the Describe Image operation in the Computer Vision service
D. the Analyze Image operation in the Computer Vision service
2. What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A. knowledgeability
B. decisiveness
C. inclusiveness
D. fairness
E. opinionatedness 3
F. reliability and safety
3. 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. increased sales
B. a reduced workload for the customer service agents
C. improved product reliability
4. You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments. This is an example of which Microsoft guiding principle for responsible AI?
A. fairness
B. inclusiveness
C. reliability and safety
D. accountability
5. For a machine learning progress, how should you split data for training and evaluation?
A. Use features for training and labels for evaluation.
B. Randomly split the data into rows for training and rows for evaluation.
C. Use labels for training and features for evaluation.
D. Randomly split the data into columns for training and columns for evaluation.
6. When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable. This is an example of which Microsoft guiding principle for responsible AI?
A. transparency
B. inclusiveness
C. fairness
D. privacy and security
7. You are building an AI system. Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?
A. Ensure that all visuals have an associated text that can be read by a screen reader.
B. Enable autoscaling to ensure that a service scales based on demand.
C. Provide documentation to help developers debug code.
D. Ensure that a training dataset is representative of the population.