Book Image

Data Science for Decision Makers

By : Howells
Book Image

Data Science for Decision Makers

By: Howells

Overview of this book

As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements. By the end of this book, you’ll be able to characterize the data within your organization and frame business problems as data science problems.
Table of Contents (20 chapters)
1
Part 1: Understanding Data Science and Its Foundations
7
Part 2: Machine Learning – Concepts, Applications, and Pitfalls
13
Part 3: Leading Successful Data Science Projects and Teams

Part 1: Understanding Data Science and Its Foundations

This part covers the foundations of data science, including key statistical concepts, data types, collection methods, exploratory data analysis, statistical significance, and regression. This part has the following chapters: