Analytical Skills for AI and Data Science

Analytical Skills for AI and Data Science

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  • Author: Daniel Vaughan
  • Publisher: O'Reilly Media
  • ISBN: 1492060917
  • Category : Computers
  • Languages : en
  • Pages : 244

While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies


Analytical Skills for AI and Data Science

Analytical Skills for AI and Data Science

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  • Author: Daniel Vaughan
  • Publisher: O'Reilly Media
  • ISBN: 9781492060949
  • Category : Computers
  • Languages : en
  • Pages : 250

While several market-leading companies have successfully transformed through data- and AI-driven approaches to business, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the potential of this predictive revolution? This practical guide presents a battle-tested method to help you translate business decisions into tractable descriptive, predictive, and prescriptive problems. Author Daniel Vaughan shows practitioners of data science and others interested in using AI not only how to ask the right questions but also how to generate value from data and analytics using modern AI technologies and decision theory principles. You'll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. With this book, you'll learn how to: Break business decisions into stages and use predictive or prescriptive methods on each stage Identify human biases when working with uncertainty Customize optimal decisions to different customers using predictive and prescriptive methods Ask business questions with high potential for value creation through AI and data-driven methods Simplify complexity to tackle difficult business decisions with current predictive and prescriptive technologies


Leading with AI and Analytics: Build Your Data Science IQ to Drive Business Value

Leading with AI and Analytics: Build Your Data Science IQ to Drive Business Value

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  • Author: Eric Anderson
  • Publisher: McGraw Hill Professional
  • ISBN: 1260459152
  • Category : Business & Economics
  • Languages : en
  • Pages : 353

Lead your organization to become evidence-driven 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. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data.


People Skills for Analytical Thinkers

People Skills for Analytical Thinkers

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  • Author: Gilbert Eijkelenboom
  • Publisher:
  • ISBN: 9789090336985
  • Category :
  • Languages : en
  • Pages : 166

Your analytical skills are incredibly valuable. However, rational thinking alone isn't enough. Have you ever: Presented an idea, but then no one seemed to care? Explained your analysis, only to leave your colleague confused? Struggled to work with people who are less analytical and more emotional? ​ In such situations, people skills make the difference. And that's what this book focuses on: boosting your communication skills as an analytical thinker. ​ Research shows people skills are becoming increasingly important in the workplace, so start learning today. ​ Filled with academic insights, exercises, and stories, this book will change your career. What you will learn ​ Having fun and productive interactions, even with people who don't have an analytical personality Boost your confidence and increase your empathy Learn how to deal with small-talk you don't enjoy Advance your communication skills and build relationships (th)at work Become incredibly persuasive by avoiding the single mistake that almost everyone makes


Data Science for Business

Data Science for Business

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  • Author: Foster Provost
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 144937428X
  • Category : Computers
  • Languages : en
  • Pages : 506

Written by renowned 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. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates


Data Science and Big Data Analytics

Data Science and Big Data Analytics

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  • Author: EMC Education Services
  • Publisher: John Wiley & Sons
  • ISBN: 1118876229
  • Category : Computers
  • Languages : en
  • Pages : 432

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!


Artificial Intelligence and Legal Analytics

Artificial Intelligence and Legal Analytics

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  • Author: Kevin D. Ashley
  • Publisher: Cambridge University Press
  • ISBN: 1107171504
  • Category : Computers
  • Languages : en
  • Pages : 451

This book describes how text analytics and computational models of legal reasoning will improve legal IR and let computers help humans solve legal problems.


Data Science

Data Science

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  • Author: Field Cady
  • Publisher: John Wiley & Sons
  • ISBN: 1119544084
  • Category : Business & Economics
  • Languages : en
  • Pages : 208

Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the "business side" of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.


Analytics, Data Science, and Artificial Intelligence

Analytics, Data Science, and Artificial Intelligence

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  • Author: Ramesh Sharda
  • Publisher:
  • ISBN: 9781292341552
  • Category : Business intelligence
  • Languages : en
  • Pages : 832

For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.


Practical Data Science with SAP

Practical Data Science with SAP

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  • Author: Greg Foss
  • Publisher: O'Reilly Media
  • ISBN: 1492046418
  • Category : Computers
  • Languages : en
  • Pages : 333

Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life