Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Harvard Business Review called data science “the sexiest job of the 21st century,” so it's no surprise that data science jobs have grown up to 20x in the last 3 years. With demand outpacing supply, companies are willing to pay top dollar for talented data professionals. However…To stand out in one of these positions, having foundational knowledge of interpreting data is essential.

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

With the world going remote, and data science following along, you can start and pursue a career in data right here, right now. How do I start? What do I need to know? What is data analytics? I'm sure one, if not all, of these questions have run through your mind. Well, the answer is data literacy: the ability to read, understand, and communicate data into information. Building a solid foundation of practical knowledge is the first step to being successful in data. From there, you can finally decide what direction you should go in and start gaining the required knowledge.

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory but made accessible through numerous real-world examples - ready for immediate application to your next graph or presentation.

Messy code is a nuisance. "Tidying" code, to make it more readable, requires breaking it up into manageable sections. In this practical guide, author Kent Beck, creator of Extreme Programming and pioneer of software patterns, suggests when and where you might apply tidyings to improve your code while keeping the overall structure of the system in mind. Instead of trying to master tidying all at once, this book lets you try out a few examples that make sense for your problem. If you have a big function containing many lines of code, you'll learn how to logically divide it into smaller chunks.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data—to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient - lessons directly applicable to your organization.

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship. Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer - but only if you work at it.

How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.

No data is completely safe. Cyberattacks on companies and individuals are on the rise and growing not only in number but also in ferocity. And while you may think your company has taken all the precautionary steps to prevent an attack, no individual, company, or country is safe. Cybersecurity can no longer be left exclusively to IT specialists. Improving and increasing data security practices and identifying suspicious activity is everyone's responsibility, from the boardroom to the break room.

Harvard Business Review called data science “the sexiest job of the 21st century,” so it's no surprise that data science jobs have grown up to 20x in the last 3 years. With demand outpacing supply, companies are willing to pay top dollar for talented data professionals. However…To stand out in one of these positions, having foundational knowledge of interpreting data is essential.

Make better decisions with this easy deconstructed guide to data analytics. Want to add data analytics to your skill stack? Having trouble finding where to start? Cell-by-cell, bit-by-bit, this audiobook teaches you the vocabulary, tools, and basic algorithms to think like a data scientist. Like putting together a complex Lego set, each section connects and adds individual blocks of knowledge to build your data literacy. This linear structure to unpacking data analytics takes you from zero to confidently analyzing and discussing data problems.

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory but made accessible through numerous real-world examples - ready for immediate application to your next graph or presentation.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

With the world going remote, and data science following along, you can start and pursue a career in data right here, right now. How do I start? What do I need to know? What is data analytics? I'm sure one, if not all, of these questions have run through your mind. Well, the answer is data literacy: the ability to read, understand, and communicate data into information. Building a solid foundation of practical knowledge is the first step to being successful in data. From there, you can finally decide what direction you should go in and start gaining the required knowledge.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

Have you ever pause and wonder why your marketing effort is not as successful as expected? Data analytics could be your answer to turn sales around. Data analytics provides the only hope for fact-based and insightful-driven decisions can help companies manage their strategic, operating and financial performance. That's why it's no longer tenable to ignore data analytics. This book has been written with a beginner in mind.

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.

The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories.

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning initiatives, aka predictive AI projects, from conception to deployment.

This audiobook will help you get ready for the changes coming in the years ahead. Listen now. Packed with expert insights, the book addresses critical questions: How will AI alter employment, education, and global geopolitics? What ethical dilemmas will arise as humans interlace with AI through cyborgs and synthetic biology? Can we prepare for superintelligence and its utopian—or dystopian—outcomes?

There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI, that has created the possibility to leverage the data of the world for the first time. The convergence of these two, with data as the common denominator, holds immense promise and the opportunities are boundless.