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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 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. 

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.

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. From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But...

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

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. 

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. 

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee.

In this book, the author discusses the various intricacies of Artificial Intelligence Fundamentals. The book is written for those with or without a technical background.

Gain a competitive edge in today’s data-driven world and build a rich career as a data professional that drives business success and innovation… Today, data is everywhere… and it has become the essential building block of this modern society. And that’s why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

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.

Turn data into decisions. Predict the future of your business — without needing a PhD. What if you could accurately predict your sales next month? Or know exactly when your website traffic will spike? Or plan your inventory, marketing, and growth with confidence instead of guesswork? 👉 Time Series Forecasting Made Simple with Python & AI is your step-by-step guide to mastering one of the most valuable skills in today’s data-driven world. This book is designed specifically for beginners, entrepreneurs, marketers, and freelancers who want real results — not complex theory. 🚀 What ...

This is a print companion to the Massive Open Online Course (MOOC), Data Structures: An Active Learning Approach (https://www.edx.org/course/data-structures-an-active-learning-approach), which utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. While this print companion contains all STOP and Think questions, which will help you reflect on the material, and all Exercise Breaks, which will test your knowledge and understanding of the concepts ...

*Start your Data Science career using Python today!* Want to begin a new lucrative career as a Data Scientist? Learn to solve real world problems using Artificial Intelligence and Machine Learning skills – with step-by-step instructions and downloadable code samples! Are you interested in becoming a Data Scientist but overwhelmed by the complexity and don’t know where to start? Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! This book is for beginners who would like to master predictive analytics and obtain a job in ...

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

Bring the world of big data into focus with "Data Science in Action." This comprehensive guide delivers a clear, definitive exploration of data science for novices and experts alike. Starting with a fascinating introduction into the world of data science, this eBook covers everything from basic definitions to the roles and responsibilities within the field. It’s time to demystify the vocabulary and discover what it really means to be a data scientist. Dive deep into the mechanics of data, understand its types, uncover the importance of data collection and learn how to manage it ...

In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve.