Welcome to the AI 900 Microsoft Azure AI Fundamentals Practice Exam

This Real Exam Training for the AI-900 Microsoft Azure AI Fundamentals Practice Tests is packed with 140+ UNIQUE practice questions.

These practice tests are designed just like the actual exam questions. Our practice tests will test your understanding of all the exam concepts which you need to pass the AI-900 Microsoft Azure AI Fundamentals exam. Its highly recommended score 90%+ on each practice test before you appear for real exam.

Key Features:

• Unlike others, We offer detailed explanations to each and every questions that will help you gain a deeper understanding of the Azure AI Fundamentals.

• Each practice exam has the same format, style, time limit and passing score as the real AI-900 Microsoft Azure AI Fundamentals certification exam.

• All questions are unique, 100% scenario-based and conform to the latest Microsoft Azure AI 900 exam blueprint.

• Every question includes a detailed explanation along with complete reference links so you can check and verify yourself that the answers are correct

• CONTAINS A TEST REPORT - to track your progress and show you which Azure knowledge areas you need improvement.

• MOBILE-COMPATIBLE - so you can conveniently review everywhere, anytime with your smartphone!

Exam AI 900: Microsoft Azure AI Fundamentals

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.

The tests cover the following AI-900 exam domains:

• Describe AI workloads and considerations (15-20%)

• Describe fundamental principles of machine learning on Azure (30-35%)

• Describe features of computer vision workloads on Azure (15-20%)

• Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)

• Describe features of conversational AI workloads on Azure (15-20%)

What is AI?

Simply put, AI is the creation of software that imitates human behaviors and capabilities. Key elements include:

• Machine learning - This is often the foundation for an AI system, and is the way we "teach" a computer model to make prediction and draw conclusions from data.

• Anomaly detection - The capability to automatically detect errors or unusual activity in a system.

• Computer vision - The capability of software to interpret the world visually through cameras, video, and images.

• Natural language processing - The capability for a computer to interpret written or spoken language, and respond in kind.

• Conversational AI - The capability of a software "agent" to participate in a conversation.