Exam Ref AI-900 Microsoft Azure AI Fundamentals (Paperback)
Language: English
Published by Pearson Education (US), Boston, 2025
- Softcover
- New
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Paperback. Prepare for Microsoft Exam AI-900 and demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) concepts, and how they can be implemented with Microsoft Azure services. 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 considerationsDescribe fundamental principles of machine learning on AzureDescribe features of computer vision workloads on AzureDescribe features of Natural Language Processing (NLP) workloads on AzureDescribe features of conversational AI workloads on Azure This Microsoft Exam Ref: Organizes its coverage by exam objectivesFeatures strategic, what-if scenarios to challenge youAssumes 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9780135417133
- Title
- Exam Ref AI-900 Microsoft Azure AI Fundamentals (Paperback)
- Author
- Julian Sharp
- Publisher
- Pearson Education (US), Boston
- Publication year
- 2025
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0135417139
- ISBN 13
- 9780135417133
- Edition
- 2nd Edition
Prepare for Microsoft Exam AI-900 and demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) concepts, and how they can be implemented with Microsoft Azure services. 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.
"Synopsis" may belong to another edition of this title.
About the Author
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.
FRANCESCO ESPOSITO, armed with a strong mathematical background, is the author of three Microsoft Press books on machine learning. He also founded Youbiquitous, an AI factory mostly working on LLMs and computer vision, and KBMS Data Force, a startup focused on digital therapy and intelligent healthcare. He is also Head of Engineering & Data at Crionet, a company that provides innovative solutions for the sport and media industries.
STEFANO COSTANZO is a computer engineer with a deep passion for artificial intelligence. He completed his Master’s degree at Tor Vergata University, where his thesis explored how large language models and information-retrieval techniques can be combined to detect fake news. Stefano approaches AI development with a solution-oriented mindset. He sees artificial intelligence as an innovative tool that can be integrated into various sectors in surprising ways, unlocking new possibilities for creative solutions.
MARTINA D’ANTONI is a software engineer with a background in clinical and biomedical engineering. Since 2021, Martina has worked in the healthcare sector, applying a blend of traditional software development and artificial intelligence to support innovation in medical technologies. Driven by curiosity and a keen interest in both data and language, she approaches problems with precision and analytical rigor. Her passion for continuous learning fuels her commitment to exploring how emerging technologies, particularly AI, can enhance patient care and shape the future of healthcare, as well as how they can more broadly support and integrate with human development.
"About the title" may belong to another edition of this title.
Grand Eagle Retail
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