Data Science Caree

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.

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.

Are you looking for an exciting and dynamic career in the tech industry? Look no further than data centers! Data centers are the backbone of the digital age. And now, with Jumpstart Your Career in Data Centers by Carrie Goetz, you can kickstart your career in this exciting field!

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.

When you're pursuing a career in a new field, or just improving your skills in hopes of finding a better job, you're going to ask yourself this question: Should I teach myself, or do online courses? In the fields of Data Science, Data Analytics, and Data Engineering, both are viable options, but you need to choose which is right for you. This strategy guide will help you decide whether online learning or the self-teaching is best for your goals, and you'll be set up for success. Don't sign up for a course or hit the books until you read this guide!

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.

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.

Read by the author. Data is not about number crunching. It’s about ideas. And when used properly (read: ethically), it is the problem solver of our time. Yet many savvy people seem to be in data denial: they don’t think they need to understand data, or it’s too complicated, or worse, using...

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.

In this clear, practical, and beginner-friendly audiobook, bestselling author Maxen Ford demystifies the world of data and shows you how to build real skills that matter in today’s job market. Data Science for Non-Techies is designed for professionals, students, and career-changers who want to understand how data drives decisions—without needing to code or memorize complex formulas.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

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.

Learn Faster. Build Skills Smarter. Launch Your Career Sooner. In today’s fast-changing job market, traditional education can’t keep up. Employers want hands-on experience, not just degrees — and bootcamps have become the fastest way to get it. The Modern Bootcamp Guide is your all-in-one roadmap to understanding, choosing, and thriving in these intensive learning programs that are transforming careers around the world. From coding and data analytics to cybersecurity, UX design, AI, and even technical trades, bootcamps now open doors across industries. This comprehensive guide ...

If you found a rusty old lamp on the beach, and upon touching it a genie appeared and granted you three wishes, what would you wish for? If you were wishing for a successful application development effort, most likely you would wish for accurate and robust data models, comprehensive data flow diagrams, and an acute understanding of human behavior. The wish for well-designed conceptual and logical data models means the requirements are well-understood and that the design has been built with flexibility and extensibility leading to high application agility and low maintenance costs. The wish ...

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.

The Science of Scaling offers a rigorous framework for founders, executives, and investors to calculate the answers using their company’s actual performance data―not wishful thinking.

Marcin Zukowski, Thierry Cruanes, and Benoit Dageville had a mission. As Snowflake’s founders, they wanted to make all types of data available to anybody with permission to use it via a simple and inexpensive mechanism. Their collective efforts drove the breakthrough creation of the Data Cloud. Snowflake’s Data Cloud platform ingests available data and transforms it into information. Without the ability to effectively process, data is just a collection of raw facts.

Two books in one - use the power of analytics and probability to discover what your target customers are thinking and how to use that as an edge in identifying solutions and strategies to help you move forward. Includes: Analytics and Probability.

If you’re considering a shift to data analysis, you’re likely exploring various programming languages to kickstart your journey. Take a cue from industry giants like Netflix, Facebook, and Amazon, who rely on SQL for data analysis. Don’t let misconceptions hinder your data analysis journey. Equip yourself with this comprehensive guide and master SQL to unlock new opportunities.

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.