9781484278239 - Managing AI in the Enterprise: Succeeding with AI Projects and MLOps to Build Sustainable AI Organizations de Haller, Klaus (23 resultados)

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Paperback. Condición: new. Paperback. Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists.For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.What You Will LearnClarify the benefits of your AI initiatives and sell them to senior managersScope and manage AI projects in your organizationSet up quality assurance and testing for AI models and their integration in complex software solutionsShape and manage an AI delivery organization, thereby mastering ML Ops Understand and formulate requirements for the underlying data management infrastructureHandle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects Who This Book Is ForExperienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organizations AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams Intermediate user level Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Taschenbuch. Condición: Neu. Managing AI in the Enterprise | Succeeding with AI Projects and MLOps to Build Sustainable AI Organizations | Klaus Haller | Taschenbuch | xix | Englisch | 2021 | Apress | EAN 9781484278239 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Condición: new. Paperback. Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists.For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.What You Will LearnClarify the benefits of your AI initiatives and sell them to senior managersScope and manage AI projects in your organizationSet up quality assurance and testing for AI models and their integration in complex software solutionsShape and manage an AI delivery organization, thereby mastering ML Ops Understand and formulate requirements for the underlying data management infrastructureHandle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects Who This Book Is ForExperienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organizations AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams Intermediate user level Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists.For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.What You Will LearnClarify the benefits of your AI initiatives and sell them to senior managersScope and manage AI projects in your organizationSet up quality assurance and testing for AI models and their integration in complex software solutionsShape and manage an AI delivery organization, thereby mastering ML OpsUnderstand and formulate requirements for the underlying data management infrastructureHandle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspectsWho This Book Is ForExperienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organization's AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams 236 pp. Englisch.

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intermediate user levelDelivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This b.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists.For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 236 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists.For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization.What You Will LearnClarify the benefits of your AI initiatives and sell them to senior managersScope and manage AI projects in your organizationSet up quality assurance and testing for AI models and their integration in complex software solutionsShape and manage an AI delivery organization, thereby mastering ML OpsUnderstand and formulate requirements for the underlying data management infrastructureHandle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspectsWho This Book Is ForExperienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organization's AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams.