Microsoft Azure AI Fundamentals (AI-900)

Categories: MicrosoftPearson Skilling Suite

This instructor-led Microsoft Azure AI Fundamentals (AI-900) course prepares you for the Microsoft Exam AI-900 while helping demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. AI-900 focuses on knowledge needed to identify features of common AI workloads and guiding principles for responsible AI; identify common ML types; describe core ML concepts; identify core tasks in creating an ML solution; describe capabilities of no-code ML with Azure Machine Learning Studio; identify common types of computer vision solutions and related Azure tools; identify features of common NLP workload scenarios and related Azure tools; and identify common use cases and Azure services for conversational AI.

The goal of this course is to provide you with all the tools you need to prepare for the AI-900 Microsoft Azure AI Fundamentals exam, including text explanations, video demos, lab activities, self-assessment questions, and a practice exam, to increase your chances of passing the exam on your first try.

Learning Outcomes:

Describe AI workloads and considerations
Describe fundamental principles of machine learning on Azure
Describe features of computer vision workloads on Azure
Describe features of Natural Language Processing (NLP) workloads on Azure
Describe features of conversational AI workloads on Azure

Optional Add-On Exam Voucher

Lesson 1: Describe Artificial Intelligence Workloads and Considerations

Identify features of common AI workloads; describe Azure services for AI and ML including Azure Machine Learning, Azure Cognitive Services, and the Azure Bot Service
Identify guiding principles for Responsible AI: Fairness; Reliability & Safety; Privacy & Security; Inclusiveness; Transparency; Accountability; Responsible AI for Bots; Microsoft’s AI for Good program

Lesson 2: Describe Fundamental Principles of Machine Learning on Azure

Identify common machine learning types: regression, classification, and clustering models
Describe core machine learning: the ML workflow; features and labels; training/validation datasets; model training algorithms; model evaluation metrics
Identify core tasks in creating a machine learning solution: Azure Machine Learning studio; data ingestion and preparation; feature selection and engineering; model training, evaluation, deployment, and management
Describe capabilities of no-code machine learning: Azure Automated Machine Learning; Azure Machine Learning designer

Lesson 3: Describe Features of Computer Vision Workloads on Azure

Identify common types of computer vision solutions: image classification; object detection; optical character recognition; facial detection, recognition, and analysis
Identify Azure tools and services for computer vision tasks: Computer Vision service; Custom Vision service; Face service; Form Recognizer service

Lesson 4: Describe Features of Natural Language Processing (NLP) Workloads on Azure

Identify features of common NLP workload scenarios: language modeling; key phrase extraction; named entity recognition; sentiment analysis; speech recognition and synthesis
Identify Azure tools and services for NLP workloads: Text Analytics service; Language Understanding service (LUIS); Speech service; Translator service

Lesson 5: Describe Features of Conversational AI Workloads on Azure

Identify common use cases for conversational AI: webchat bots and their features and uses
Identify Azure services for conversational AI: QnA Maker service; Azure Bot Service

Suitable for

Designed for business stakeholders, new and existing IT professionals, consultants, and students; focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level

Pre-requisite

Basic knowledge of operating systems and computer networks
Familiarity with the usage of the Internet and web browsers

Duration

Certificate

Microsoft Certified: Azure AI Fundamentals

Governing Body

Microsoft

Examination Body

Pearson VUE

SKILLING SUITE FEATURES

In-Demand And Up To Date Courseware

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Live Contextualised Labs

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Practice Tests And Exam Pass Pledge

Help learners increase their certification readiness with practice tests designed to improve pass rates. If needed, our Exam Pass Pledge means you can give learners a free retake within 30 days of passing their last practice test.