RED HAT CERTIFICATION
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Prepare for Microsoft Exam AI-900 and help demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. Designed for business stakeholders, new and existing IT professionals, consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level.
Focus on the expertise measured by these objectives:
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
This Microsoft Exam Ref:
Organizes its coverage by exam objectives
Features strategic, what-if scenarios to challenge you
Assumes you are a business user, stakeholder, technical professional, or student who wants to become familiar with Azure AI; requires no data science or software engineering experience.
About the Exam
Exam 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; identify Azure tools and services for computer vision tasks; identify features of common NLP workload scenarios; identify Azure tools and services for NLP workloads; and identify common use cases and Azure services for conversational Al.
About Microsoft Certification
Passing this exam fulfills your requirements for the Microsoft Certified: Azure AI Fundamentals certification, demonstrating your knowledge of common ML and AI workloads and how to implement them on Azure. With this certification, you can move on to earn more advanced role-based certifications, including Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate.
See full details at: microsoft.com/learn
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CHAPTER 1 Describe Artificial Intelligence workloads and considerations
CHAPTER 2 Describe fundamental principles of machine learning on Azure
CHAPTER 3 Describe features of computer vision workloads on Azure
CHAPTER 4 Describe features of Natural Language Processing (NLP) workloads on Azure
CHAPTER 5 Describe features of conversational AI workloads on Azure