Microsoft Azure AI Fundamentals AI-900 Exam Guide (Early Access)

Learn how to develop and implement AI/ML based solutions in Azure cloud environment and pass the Microsoft's Azure AI Fundamentals (AI-900) certification exam with ease

Key Features
Learn about the different features and types of Azure AI services, namely, Computer Vision, Automated Machine Learning, NLP, and OpenAI
Understand common AI use cases such as image identification, prediction, sentiment analysis, and chatbots
Self-check your knowledge with two full-length mock exams
Purchase of the print or Kindle book includes a free PDF eBook

Book Description
Microsoft's Azure AI Fundamentals (AI-900) certification exam offers a comprehensive overview of key AI-related topics and tools used to work with AI solutions in the Azure cloud. It helps you to take your first step into an AI-shaped future regardless of your technical background.

This exam guide explains the AI workloads including natural language processing (NLP) and large language models (LLMs) like ChatGPT. You’ll explore Microsoft's responsible AI principles like safety, accountability, etc. You’ll understand the basics of machine learning (ML), including classification and deep learning and how to use training and validation datasets with Azure ML. Using Azure AI Vision, Face Detection, and Video Indexer services, you’ll understand computer vision related topics like image classification, object and facial detection, etc. You’ll learn about NLP features like key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, Speech, and Translator services. You’ll deep dive into identifying generative AI models and leveraging the Azure OpenAI Service for content generation. You'll be able to test your understanding of the topics covered with the help of mock exams.

After reading this exam guide, you’ll be equipped to work with AI solutions in Azure and be well-prepared to pass the AI-900 exam.

What you will learn
Discusses various types of Artificial Intelligence (AI) workloads and services in Azure
Covers Microsoft's guiding principles for responsible AI development and use
Includes fundamental principles of how AI and machine learning work
Explains how AI models can recognize content in images and documents
Details the features and use cases for Natural Language Processing (NLP)
Explores the capability of generative AI services

Who this book is for
Whether you're a cloud engineer, software developer or an aspiring data scientist, or any non-technical person interested in learning AI/ML concepts and capabilities on Azure, then this book is for you. In addition, it serves as a foundation for those wishing to appear for more advanced AI and Data Science related certification exams (e.g. Microsoft Certified: Azure AI Engineer Associate). For using this book, you’re not required to have experience in data science and software engineering. However, it is assumed that you have a basic knowledge of cloud concepts and client-server applications.

Table of Contents
Identify features of common AI workloads
Identify guiding principles for responsible AI
Identify common machine learning techniques
Describe core machine learning concepts
Describe Azure Machine Learning capabilities
Identify common types of computer vision solution
Identify Azure tools and services for computer vision tasks
Identify features of common NLP Workload Scenarios
Identify Azure tools and services for NLP workloads
Identify features of generative AI solutions
Identify capabilities of Azure OpenAI Service
Mock Exam #1
Mock Exam #2