AI and the Project Manager: How the Rise of Artificial Intelligence Will Change Your World
- Length: 158 pages
- Edition: 1
- Language: English
- Publisher: Routledge
- Publication Date: 2021-10-28
- ISBN-10: 1032006560
- ISBN-13: 9781032006567
- Sales Rank: #0 (See Top 100 Books)
Enabling project managers to adapt to the new technology of artificial intelligence, this first comprehensive book on the topic discusses how AI will reinvent the project world and allow project managers to focus on people.
Studies show that by 2030, 80 percent of project management tasks, such as data collection, reporting, and predictive analysis, will be carried out by AI in a consistent and efficient manner. This book sets out to explore what this will mean for project managers around the world and equips them to embrace this technological advantage for greater project success.
Filled with insights and examples from tech providers and project experts, this book is an invaluable resource for PMO leaders, change executives, project managers, programme managers, and portfolio managers. Anyone who is part of the global community of change and project leadership needs to accept and understand the fast- approaching AI technology, and this book shows how to use it to their advantage.
Cover Half Title Series Page Title Page Copyright Page Contents Preface Editors Contributors 1. Introduction 1.1 Why this book? 1.2 Defining big data and its value 1.3 The importance of inference 1.3.1 Description 1.3.2 Causation 1.3.3 Prediction 1.4 The importance of understanding how data are generated 1.5 New tools for new data 1.6 The book’s “use case” 1.7 The structure of the book 1.7.1 Part I: Capture and curation 1.7.2 Part II: Modeling and analysis 1.7.3 Part III: Inference and ethics 1.8 Resources Part I Capture and Curation 2 Working with Web Data and APIs 3 Record Linkage 4 Databases 5 Scaling up through Parallel and Distributed Computing Part II Modeling and Analysis 6 Information Visualization 7 Machine Learning 8 Text Analysis 9 Networks: The Basics Part III Inference and Ethics 10 Data Quality and Inference Errors 11 Bias and Fairness 12 Privacy and Confidentiality 13 Workbooks 334_Password_Removed Bibliography Index
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