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Microsoft Azure AI Fundamentals AI-900 Exam Guide
Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide : Gain proficiency in Azure AI and machine learning concepts and services to excel in the AI-900 exam

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Profile Icon Aaron Guilmette Profile Icon Steve Miles
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$24.99 $35.99
Book May 2024 288 pages 1st Edition
eBook
$24.99 $35.99
Print
$44.99
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Renews at $19.99p/m
Arrow left icon
Profile Icon Aaron Guilmette Profile Icon Steve Miles
Arrow right icon
$24.99 $35.99
Book May 2024 288 pages 1st Edition
eBook
$24.99 $35.99
Print
$44.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$24.99 $35.99
Print
$44.99
Subscription
Free Trial
Renews at $19.99p/m

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Microsoft Azure AI Fundamentals AI-900 Exam Guide

Part 1: Identify Features of Common AI Workloads

In this first part of the book, you will be introduced to foundational concepts of artificial intelligence (AI) workloads as well as Microsoft’s principles for responsible AI development.

This part includes the following chapters:

  • Chapter 1, Identify Features of Common AI Workloads
  • Chapter 2, Identify the Guiding Principles for Responsible AI
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Key benefits

  • Discover Azure AI services, including computer vision, Auto ML, NLP, and OpenAI
  • Explore AI use cases, such as image identification, chatbots, and more
  • Work through 145 practice questions under chapter-end self-assessments and mock exams
  • Purchase of this book unlocks access to web-based exam prep resources, including mock exams, flashcards, and exam tips

Description

The AI-900 exam helps you take your first step into an AI-shaped future. Regardless of your technical background, this book will help you test your understanding of the key AI-related topics and tools used to develop AI solutions in Azure cloud. This exam guide focuses on AI workloads, including natural language processing (NLP) and large language models (LLMs). You’ll explore Microsoft’s responsible AI principles like safety and accountability. Then, you’ll cover the basics of machine learning (ML), including classification and deep learning, and learn how to use training and validation datasets with Azure ML. Using Azure AI Vision, face detection, and Video Indexer services, you’ll get up to speed with computer vision-related topics like image classification, object detection, and facial detection. Later chapters cover NLP features such as key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, speech, and translator services. The book also guides you through identifying GenAI models and leveraging Azure OpenAI Service for content generation. At the end of each chapter, you’ll find chapter review questions with answers, provided as an online resource. By the end of this exam guide, you’ll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources.

What you will learn

  • Discover various types of artificial intelligence (AI)workloads and services in Azure
  • Cover Microsoft's guiding principles for responsible AI development and use
  • Understand the fundamental principles of how AI and machine learning work
  • Explore how AI models can recognize content in images and documents
  • Gain insights into the features and use cases for natural language processing
  • Explore the capabilities of generative AI services

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 31, 2024
Length 288 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781835885666
Category :
Languages :
Tools :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
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Product feature icon Access this title in our online reader with advanced features
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Product Details

Publication date : May 31, 2024
Length 288 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781835885666
Category :
Languages :
Tools :

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Table of Contents

20 Chapters
Preface Chevron down icon Chevron up icon
1. Part 1: Identify Features of Common AI Workloads Chevron down icon Chevron up icon
2. Chapter 1: Identify Features of Common AI Workloads Chevron down icon Chevron up icon
3. Chapter 2: Identify the Guiding Principles for Responsible AI Chevron down icon Chevron up icon
4. Part 2: Describe the Fundamental Principles of Machine Learning on Azure Chevron down icon Chevron up icon
5. Chapter 3: Identify Common Machine Learning Techniques Chevron down icon Chevron up icon
6. Chapter 4: Describe Core Machine Learning Concepts Chevron down icon Chevron up icon
7. Chapter 5: Describe Azure Machine Learning Capabilities Chevron down icon Chevron up icon
8. Part 3: Describe Features of Computer Vision Workloads on Azure Chevron down icon Chevron up icon
9. Chapter 6: Identify Common Types of Computer Vision Solutions Chevron down icon Chevron up icon
10. Chapter 7: Identify Azure Tools and Services for Computer Vision Tasks Chevron down icon Chevron up icon
11. Part 4: Describe Features of Natural Language Processing (NLP) Workloads on Azure Chevron down icon Chevron up icon
12. Chapter 8: Identify Features of Common NLP Workload Scenarios Chevron down icon Chevron up icon
13. Chapter 9: Identify Azure Tools and Services for NLP Workloads Chevron down icon Chevron up icon
14. Part 5: Describe Features of Generative AI Workloads on Azure Chevron down icon Chevron up icon
15. Chapter 10: Identify Features of Generative AI Solutions Chevron down icon Chevron up icon
16. Chapter 11: Identify Capabilities of Azure OpenAI Service Chevron down icon Chevron up icon
17. Chapter 12: Accessing the Online Practice Resources Chevron down icon Chevron up icon
18. Index Chevron down icon Chevron up icon
19. Other Books You May Enjoy Chevron down icon Chevron up icon
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