Preface

Data science, machine learning, and artificial intelligence (AI) are transforming the business landscape.

Organizations in every industry are harnessing these powerful tools to uncover insights, make predictions, and gain a competitive edge. This trend has only accelerated with the rise in large language models and Generative AI.

But for decision makers without a data science background, or those stepping up from being a data scientist to leading data teams, there are a myriad of challenges. It can be challenging to understand underlying concepts of statistics, machine learning, and AI; manage data teams effectively; and, most importantly, translate complex models into tangible business outcomes – business outcomes that deliver real, bottom-line value to an organization, not just vanity metrics and shiny demos.

This book is your guide. In Data Science for Decision Makers, you’ll gain the essential knowledge and skills to lead in the age of AI. Through clear explanations and practical examples, you’ll learn how to interpret machine learning models, identify valuable use cases, and drive measurable results. Step by step, you’ll learn the foundations of statistics and machine learning. You’ll discover how to plan and execute successful data science initiatives from start to finish.

Along the way, you’ll pick up best practices for building and empowering high-performing teams. Most importantly, you’ll learn how to bridge the gap between the technical world of data science and the business needs of your organization. Whether you’re an executive, a manager, or a data scientist moving into leadership, this book will help you leverage data-driven insights to inform your decisions and propel your company forward.