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Actualkey Prepration Latest AI-900 : Microsoft Azure AI Fundamentals (beta) Exam Questions and Answers PDF's, Verified Answers via Experts - Pass Your Exam For Sure and instant Downloads - "Money Back Guarantee".
| Vendor | Microsoft |
| Certification | Microsoft Certified: Azure AI Fundamentals |
| Exam Code | AI-900 |
| Title | Microsoft Azure AI Fundamentals (beta) Exam |
| No Of Questions | 276 |
| Last Updated | October 23,2024 |
| Product Type | Q & A with Explanation |
| Bundel Pack Included | PDF + Offline / Andriod Testing Engine and Simulator |
Study guide for Exam AI-900: Microsoft Azure AI Fundamentals
Audience profile
This exam is an opportunity to demonstrate knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services. Candidates for this exam should have familiarity with AI-900’s self-paced or instructor-led learning material.
This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, awareness of cloud basics and client-server applications 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 is not a prerequisite for any of them.
Skills at a glance
Describe Artificial Intelligence workloads and considerations (20–25%)
Describe fundamental principles of machine learning on Azure (25–30%)
Describe features of computer vision workloads on Azure (15–20%)
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Describe Artificial Intelligence workloads and considerations (20–25%)
Identify features of common AI workloads
Identify features of anomaly detection workloads
Identify computer vision workloads
Identify natural language processing workloads
Identify knowledge mining workloads
Identify guiding principles for responsible AI
Describe considerations for fairness in an AI solution
Describe considerations for reliability and safety in an AI solution
Describe considerations for privacy and security in an AI solution
Describe considerations for inclusiveness in an AI solution
Describe considerations for transparency in an AI solution
Describe considerations for accountability in an AI solution
Describe fundamental principles of machine learning on Azure (25–30%)
Identify common machine learning types
Identify regression machine learning scenarios
Identify classification machine learning scenarios
Identify clustering machine learning scenarios
Describe core machine learning concepts
Identify features and labels in a dataset for machine learning
Describe how training and validation datasets are used in machine learning
Describe capabilities of visual tools in Azure Machine Learning Studio
Automated machine learning
Azure Machine Learning designer
Describe features of computer vision workloads on Azure (15–20%)
Identify common types of computer vision solution
Identify features of image classification solutions
Identify features of object detection solutions
Identify features of optical character recognition solutions
Identify features of facial detection and facial analysis solutions
Identify Azure tools and services for computer vision tasks
Identify capabilities of the Computer Vision service
Identify capabilities of the Custom Vision service
Identify capabilities of the Face service
Identify capabilities of the Form Recognizer service
Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
Identify features of common NLP Workload Scenarios
Identify features and uses for key phrase extraction
Identify features and uses for entity recognition
Identify features and uses for sentiment analysis
Identify features and uses for language modeling
Identify features and uses for speech recognition and synthesis
Identify features and uses for translation
Identify Azure tools and services for NLP workloads
Identify capabilities of the Language service
Identify capabilities of the Speech service
Identify capabilities of the Translator service
Identify considerations for conversational AI solutions on Azure
Identify features and uses for bots
Identify capabilities of Power Virtual Agents and the Azure Bot service
Exam Guide:
Total number of question will be present around 40 to 60 questions with a timeline of 60 minutes in exam.
To pass the exam candidate must score 700 marks out of 1000.
What you’ll learn
This Practice Test which will help clear the Azure AI-900 Fundamentals Certification Exam with Good Score.
Real Exam Simulation with 6 Practice Tests Series.
This Test Series Contain Total 360 Questions and Answer with Detail Explanation.
Lifetime access with every latest updates.
Are there any course requirements or prerequisites?
PC/Laptop or Smart Phone and Internet Connection
Who this course is for:
Preparing or appearing to get Microsoft Azure AI-900: AI Fundamentals Certification.
Any one planning(both technical and non-technical backgrounds) wanting to kick start their journey in Machine Learning and Artificial Intelligence domain.
Interested to learn the fundamentals of AI and ML with Azure.
Sample Questions
QUESTION 1
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
Answer: B
QUESTION 2
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.
Answer: B
QUESTION 3
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?
A. Set Validation type to Auto.
B. Enable Explain best model.
C. Set Primary metric to accuracy.
D. Set Max concurrent iterations to 0.
Answer: B
QUESTION 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
Answer: B
Students Reviews / Discussion
Arun Kumar 2 months, 1 week ago - United States
hello, took exam today and passed , i got 97% questions and all were found here.
upvoted 1 times
Chrysovalantis Papachristos 3 months, 1 week ago - Switzerland
Passed today. 90% of the questions are included here. I got only from the last 100 questions
upvoted 2 times
Daffa Ulwan 3 months, 2 weeks ago - Indonesia
Passed the exam. 80% of the exam are on this reviewer
upvoted 5 times
çer raziye2 months ago - Turkey
Just passed SVPN - Felt like 90% of these questions were on the exam. I only had a few questions that weren't here. I spent a lot of time verifying answers to the questions here because many are incorrect. Just pay attention to the discussion posts from people but the questions/options are spot on. - February 2023
upvoted 3 times
Vigo Carrillo 8 months, 3 weeks ago - Spain
same here. only 1 was not from these dumps!
upvoted 1 times
Miguel White 3 months ago - United States
These questions are still valid, thanks.
upvoted 4 times
Temmy Tope 6 months ago - South Africa
These questions are stull valid.
upvoted 4 times
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