Managing AI in the Enterprise: Succeeding with AI Projects and MLOps to Build Sustainable AI Organizations

Author:   Klaus Haller
Publisher:   APress
Edition:   1st ed.
ISBN:  

9781484278239


Pages:   214
Publication Date:   17 December 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Managing AI in the Enterprise: Succeeding with AI Projects and MLOps to Build Sustainable AI Organizations


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Overview

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 Learn Clarify the benefits of your AI initiatives and sell them to senior managers Scope and manage AI projects in your organization Set up quality assurance and testing for AI models and their integration in complex software solutions Shape and manage an AI delivery organization, thereby mastering ML Ops  Understand and formulate requirements for the underlying data management infrastructure Handle 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 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

Full Product Details

Author:   Klaus Haller
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.456kg
ISBN:  

9781484278239


ISBN 10:   1484278232
Pages:   214
Publication Date:   17 December 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Why Organizations Invest in AI2. Structuring and Delivering AI Projects3. Quality Assurance in and for AI4. Ethics, Regulations, and Explainability5. Building an AI Delivery Organization6. AI & Data Management Architectures 7. Securing & Protecting AI Environments 8. Looking Forward

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Author Information

Klaus Haller is a senior IT architect and IT project manager with more than 15 years of experience in the IT industry. Originally from Germany, he has called Zurich, Switzerland home for many years. He currently works as a senior security architect for a global insurance company, focusing on protecting public cloud infrastructures and data management and AI environments. Klaus is passionate about designing complex solutions that fit into corporate application landscapes. He understands the interplay between technology, operations, engineering, and the business from his previous experience in various roles such as software engineer, project and product manager, business analyst, process engineer, and solutions architect. His expertise includes core banking systems and credit applications, databases, data analytics and artificial intelligence, data migration, public cloud, IT security, and IT risk management. He loves the outdoors and enjoys writing for magazines and online blogs and speaking at conferences and seminars. 

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