Data Science Career

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.

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.

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.

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way.

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.

Data. It's the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries.

Data science gets thrown around in the press like it's magic. Major retailers are predicting everything, from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. Data science is little more than using straightforward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will teach how you how that's done within the familiar environment of a spreadsheet.

How organizations can deliver significant performance gains through strategic investment in marketing.

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...

In the age of Big Data we often believe that our predictions about the future are better than ever before. But as risk expert Gerd Gigerenzer shows, the surprising truth is that in the real world, we often get better results by using simple rules and considering less information. In Risk Savvy, Gigerenzer reveals that most of us, including doctors, lawyers, financial advisers, and elected officials, misunderstand statistics much more often than we think, leaving us not only misinformed, but vulnerable to exploitation.

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, this book presents ninety-seven concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data.

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.

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.

This book walks you through the "need-to-know" aspects of artificial intelligence, including natural language processing, speech recognition, and the power of machine learning to show you how to make the most of this technology in a practical, tactical way. Case studies show how real-world companies are taking the next leap forward. Artificial intelligence and machine learning provide a data-driven basis for more robust and intensely-targeted marketing strategies - and companies that effectively utilize these latest tools will reap the benefit in the marketplace.

From facial recognition—capable of checking us onto flights or identifying undocumented residents—to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search.

Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments - also known as randomized controlled trials - designed to test the impact of different online experiences. In this book, Michael Luca and Max Bazerman explain the importance of experiments for decision making in a data-driven world.

What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Drawing upon real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.

Cómo tomar decisiones estratégicas a partir de la analítica de datos. "¿Cuál es la función de los datos, entonces, y de su análisis profundo y racional antes de tomar una decisión en una empresa o en una organización?... ¿Quiénes toman las decisiones en una empresa? ¿Qué decisiones toman?", se pregunta el autor de este libro que invita a líderes de equipos de trabajo a pensar en un término muy presente hoy: la data. Y, sobre todo, qué hacer con ella.

Data Leadership for Everyone is a game-changing book for anyone who believes in the power of data and is ready to create revolutionary change in their organization. Whether you're a C-suite executive, a manager, or an individual contributor, this book will propel your career by unlocking the mystery of how raw data transforms into real outcomes.

Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of big data. Listeners are guided through tried-and-true methodologies for getting more out of data and using it to the utmost advantage. This audiobook describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding big data, all while guiding listeners toward better decision-making from the perspective of a data scientist.