Exam Ref AI-900 Microsoft Azure AI Fundamentals

 
 
Pearson Education (US) (Verlag)
  • 1. Auflage
  • |
  • erschienen am 16. November 2021
  • |
  • 208 Seiten
 
E-Book | ePUB mit Adobe-DRM | Systemvoraussetzungen
978-0-13-735814-4 (ISBN)
 
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
 

<b>Prepare for Microsoft Exam AI-900</b> 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.

<b>Focus on the expertise measured by these objectives: </b>

* 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


<b>This Microsoft Exam Ref:</b>

* 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.

<b>About the Exam</b>

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.

<b>About Microsoft Certification</b>

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.


<b>See full details at: microsoft.com/learn</b>

1. Auflage
  • Englisch
  • Upper Saddle River
  • |
  • USA
  • Für Beruf und Forschung
978-0-13-735814-4 (9780137358144)

weitere Ausgaben werden ermittelt
JULIAN SHARP is a solutions architect, trainer, and Microsoft Business Applications MVP with over 30 years of experience in IT. He completed his MA in Mathematics at the University of Cambridge. Julian has spoken at Microsoft Ignite and many other community events. For the past 15 years, he has been a Microsoft Certified Trainer delivering certification training around Dynamics 365, Azure, and the Power Platform. He has taught thousands of students with a high pass rate. Julian has a passion for Artificial Intelligence to enhance user experience and customer data in the solutions that he designs.

<b>JULIAN SHARP</b> is a solutions architect, trainer, and Microsoft Business Applications MVP with over 30 years of experience in IT. He completed his MA in Mathematics at the University of Cambridge. Julian has spoken at Microsoft Ignite and many other community events. For the past 15 years, he has been a Microsoft Certified Trainer delivering certification training around Dynamics 365, Azure, and the Power Platform. He has taught thousands of students with a high pass rate. Julian has a passion for Artificial Intelligence to enhance user experience and customer data in the solutions that he designs.

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


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