Praise for Demystifying Technical Training "Demystifying Technical Training is a must-read for CLOs, managers of training, instructors, and instructional designers. All who read it will gain critical insights into how to lower the cost and improve the efficiency and effectiveness of learning." —Wm. Douglas Harward, CEO and founder of Training Industry, Inc. "Individuals interested in and accountable for deriving significant value from technical training investments will gain great benefit from reading this book and applying its wisdom." —Karen Kocher, CLO at Cigna Healthcare "Demystifying Technical Training is an essential, complete guide for any learning organization. The overviews and concepts are clearly stated, while the case studies and sidebars provide practical examples you can apply in your situation." —Jean Barbazette, president of The Training Clinic and author of Managing the Training Function for Bottom-Line Results "Considering the cost of acquiring and developing talent, why wouldn't all CEO/COOs insist on investing in people to improve results and reduce risk? This book demystifies the process of developing technical experts to increase the return on investment in human capital. Bravo!" —Martin J. Menard, former group CIO at Intel Corporation "Technical training is a key to sustaining competitiveness in the new economy. Learn how to leverage and optimize its value in your organization through this wonderfully insightful and practical resource." —Dr. Arthur L. Jue, director of global organization and talent development at Oracle and co-author of Social Media at Work: How Networking Tools Propel Organizational Performance "Don't be misled by the title—this book—while focusing on the often segmented world of domain specific job skills—provides guidance valid for the full spectrum of workforce learning from soft-skills to 'technical' skills." —Ruth Clark, principal and president of Clark Training & Consulting and author of e-Learning and the Science of Instruction

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. - Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies - Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics - Unique case study approach provides readers with insights for practical clinical implementation

This book presents a solid, research-based conceptual framework that demystifies organizational learning and bridges the gap between theory and practice. Using an integrative approach, authors Raanan Lipshitz, Victor Friedman and Micha Popper provide practitioners and researchers with tools for understanding organizational learning under real-world conditions.

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

The 'BrainCanDo' Handbook of Teaching and Learning provides teachers and school leaders with a concise summary of how some of the latest research in educational neuroscience and psychology can improve learning outcomes. It aims to create a mechanism through which our growing understanding of the brain can be applied in the world of education. Subjects covered include memory, social development, mindsets and character. Written by practising teachers working in collaboration with researchers, the chapters provide a toolkit of practical ideas which incorporate evidence from psychology and neuroscience into teaching practice with the aim of improving educational outcomes for all. By increasing both teachers’ and pupils’ understanding of the developing brain, ‘BrainCanDo’ aims to improve cognitive performance and attainment, foster a love of learning and enable a healthy and productive approach to personal development. This book will appeal to educators, primarily those working in secondary schools, but also those within higher and primary school education. It will also be of interest to students of education, professionals looking to enhance their teaching and researchers working in the fields of education, psychology and neuroscience.

Informative, insightful, and accessible, this book is designed to enhance the capacity of graduate and undergraduate students, as well as early career scholars, to write for academic purposes. Fang describes key genres of academic writing, common rhetorical moves associated with each genre, essential skills needed to write the genres, and linguistic resources and strategies that are functional and effective for performing these moves and skills. Fang’s functional linguistic approach to academic writing enables readers to do so much more than write grammatically well-formed sentences. It leverages writing as a process of designing meaning to position language choices as the central focus, illuminating how language is a creative resource for presenting information, developing argument, embedding perspectives, engaging audience, and structuring text across genres and disciplines. Covering reading responses, book reviews, literature reviews, argumentative essays, empirical research articles, grant proposals, and more, this text is an all-in-one resource for building a successful career in academic writing and scholarly publishing. Each chapter features crafts for effective communication, authentic writing examples, practical applications, and reflective questions. Fang complements these features with self-assessment tools for writers and tips for empowering writers. Assuming no technical knowledge, this text is ideal for both non-native and native English speakers, and suitable for courses in academic writing, rhetoric and composition, and language/literacy education.

Technology is viewed as a powerful force both in and out of school and has long been linked with math and science. Although concepts and activities of this book apply to any grade, the primary focus is on the elementary and middle school levels. This book provides principles and practical strategies for promoting creative and innovative work in math, science, and technology. The authors pay close attention to the social nature of learning and how collaboration can spark student interest in open-ended problem-solving. Shining a light on mathematic, scientific, and technological processes gives everyone more control over what is going on around them and increases understanding of how things work.

Demystifying Talent Management offers practical advice for all managers, HR professionals, senior leaders, and other employees on how to work together to build a talented and motivated workforce. The book addresses performance, development, coaching, feedback, compensation, and other elements of people management. Using simple, straightforward language, Kim Janson tells you how you can avoid confusion and conflicts when engaging in talent management. You'll learn: What performance is needed and expected: how to translate your company's strategy into individual performance; What it means to measure and track progress, simply and clearly; What you can and should do to help an individual's development; How to narrow your focus to improve a skill, knowledge, or experience; How to take both an individual's profile and the direction of the organization into account in career development and succession planning; How to make compensation (cash, public accolades, feedback, etc.) a true driver of results; How coaching and feedback are essential in bringing all the elements of talent management together. This book will guide you to a deeper understanding of the mechanics of talent management and development success so that all the stakeholders can come together in a win-win-win-win scenario.

The purpose of this book is to clearly define an approach to school improvement that uses professional learning community (PLC) practices to achieve school improvement and success for every student. This book offers information, examples and case studies to clarify the concept of a PLC, to respond to critical issues in schools, and to support educational leaders in addressing the important mandates of accountability and school improvement. As school leaders proactively lead efforts to create learning communities, their schools, districts, and staff will incorporate knowledge, skills, and practices that focus on teaching and learning for all. The authors' findings will assist leaders, change agents, policy makers, and university faculty in guiding schools toward creating and maintaining PLCs as they sustain school improvement for student learning.