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| carnegie mellon data science masters acceptance rate: Business Trends in Practice Bernard Marr, 2021-11-15 WINNER OF THE BUSINESS BOOK OF THE YEAR AWARD 2022! Stay one step ahead of the competition with this expert review of the most impactful and disruptive business trends coming down the pike Far from slowing down, change and transformation in business seems to come only at a more and more furious rate. The last ten years alone have seen the introduction of groundbreaking new trends that pose new opportunities and challenges for leaders in all industries. In Business Trends in Practice: The 25+ Trends That Are Redefining Organizations, best-selling business author and strategist Bernard Marr breaks down the social and technological forces underlying these rapidly advancing changes and the impact of those changes on key industries. Critical consumer trends just emerging today—or poised to emerge tomorrow—are discussed, as are strategies for rethinking your organisation’s product and service delivery. The book also explores: Crucial business operations trends that are changing the way companies conduct themselves in the 21st century The practical insights and takeaways you can glean from technological and social innovation when you cut through the hype Disruptive new technologies, including AI, robotic and business process automation, remote work, as well as social and environmental sustainability trends Business Trends in Practice: The 25+ Trends That Are Redefining Organizations is a must-read resource for executives, business leaders and managers, and business development and innovation leads trying to get – and stay – on top of changes and disruptions that are right around the corner. |
| carnegie mellon data science masters acceptance rate: GRE Prep by Magoosh Magoosh, Chris Lele, Mike McGarry, 2016-12-07 Magoosh gives students everything they need to make studying a breeze. We've branched out from our online GRE prep program and free apps to bring you this GRE prep book. We know sometimes you don't have easy access to the Internet--or maybe you just like scribbling your notes in the margins of a page! Whatever your reason for picking up this book, we're thrilled to take this ride together. In these pages you'll find: --Tons of tips, FAQs, and GRE strategies to get you ready for the big test. --More than 130 verbal and quantitative practice questions with thorough explanations. --Stats for each practice question, including its difficulty rating and the percent of students who typically answer it correctly. We want you to know exactly how tough GRE questions tend to be so you'll know what to expect on test day. --A full-length practice test with an answer key and detailed explanations. --Multiple practice prompts for the analytical writing assessment section, with tips on how to grade each of your essays. If you're not already familiar with Magoosh online, here's what you need to know: --Our materials are top-notch--we've designed each of our practice questions based on careful analysis of millions of students' answers. --We really want to see you do your best. That's why we offer a score improvement guarantee to students who use the online premium Magoosh program. --20% of our students earn a top 10% score on the GRE. --Magoosh students score on average 12 points higher on the test than all other GRE takers. --We've helped more than 1.5 million students prepare for standardized tests online and with our mobile apps. So crack open this book, join us online at magoosh.com, and let's get you ready to rock the GRE! |
| carnegie mellon data science masters acceptance rate: Data Science Careers, Training, and Hiring Renata Rawlings-Goss, 2019-08-02 This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build. |
| carnegie mellon data science masters acceptance rate: The Last Lecture Randy Pausch, Jeffrey Zaslow, 2010 The author, a computer science professor diagnosed with terminal cancer, explores his life, the lessons that he has learned, how he has worked to achieve his childhood dreams, and the effect of his diagnosis on him and his family. |
| carnegie mellon data science masters acceptance rate: The Enlightened College Applicant Andrew Belasco, Dave Bergman, 2023-05-15 Deluged with messages that range from “It’s Ivy League or bust” to “It doesn’t matter where you go,” college applicants and their families often find themselves lost, adrift in a sea of information overload. Finally—a worthy life preserver has arrived. The Enlightened College Applicant speaks to its audience in a highly accessible, engaging, and example-filled style, giving readers the perspective and practical tools to select and earn admission at the colleges that most closely align with their academic, career, and life goals. In place of the recycled entrance statistics or anecdotal generalizations about campus life found in many guidebooks, The Enlightened College Applicant presents a no-nonsense account of how students should approach the college search and admissions process. Shifting the mindset from “How can I get into a college?” to “What can that college do for me?” authors Bergman and Belasco pull back the curtain on critical topics such as whether college prestige matters, what college-related skills are valued in the job market, which schools and degrees provide the best return on investment, how to minimize the costs of a college education, and much more. Whether you are a valedictorian or a B/C student, this easy-to-read book will improve your college savvy and enable you to maximize the benefits of your higher education. |
| carnegie mellon data science masters acceptance rate: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| carnegie mellon data science masters acceptance rate: Capital Ideas Evolving Peter L. Bernstein, 2011-01-31 A lot has happened in the financial markets since 1992, when Peter Bernstein wrote his seminal Capital Ideas. Happily, Peter has taken up his facile pen again to describe these changes, a virtual revolution in the practice of investing that relies heavily on complex mathematics, derivatives, hedging, and hyperactive trading. This fine and eminently readable book is unlikely to be surpassed as the definitive chronicle of a truly historic era. John C. Bogle, founder of The Vanguard Group and author, The Little Book of Common Sense Investing Just as Dante could not have understood or survived the perils of the Inferno without Virgil to guide him, investors today need Peter Bernstein to help find their way across dark and shifting ground. No one alive understands Wall Street's intellectual history better, and that makes Bernstein our best and wisest guide to the future. He is the only person who could have written this book; thank goodness he did. Jason Zweig, Investing Columnist, Money magazine Another must-read from Peter Bernstein! This well-written and thought-provoking book provides valuable insights on how key finance theories have evolved from their ivory tower formulation to profitable application by portfolio managers. This book will certainly be read with keen interest by, and undoubtedly influence, a wide range of participants in international finance. Dr. Mohamed A. El-Erian, President and CEO of Harvard Management Company, Deputy Treasurer of Harvard University, and member of the faculty of the Harvard Business School Reading Capital Ideas Evolving is an experience not to be missed. Peter Bernstein's knowledge of the principal characters-the giants in the development of investment theory and practice-brings this subject to life. Linda B. Strumpf, Vice President and Chief Investment Officer, The Ford Foundation With great clarity, Peter Bernstein introduces us to the insights of investment giants, and explains how they transformed financial theory into portfolio practice. This is not just a tale of money and models; it is a fascinating and contemporary story about people and the power of their ideas. Elroy Dimson, BGI Professor of Investment Management, London Business School Capital Ideas Evolving provides us with a unique appreciation for the pervasive impact that the theory of modern finance has had on the development of our capital markets. Peter Bernstein once again has produced a masterpiece that is must reading for practitioners, educators and students of finance. Andr F. Perold, Professor of Finance, Harvard Business School |
| carnegie mellon data science masters acceptance rate: What It Feels Like Stephanie R. Larson, 2021-07-15 Winner of the 2022 Association for the Rhetoric of Science, Technology, and Medicine (ARSTM) Book Award Winner of the 2022 Winifred Bryan Horner Outstanding Book Award from the Coalition of Feminist Scholars in the History of Rhetoric and Composition What It Feels Like interrogates an underexamined reason for our failure to abolish rape in the United States: the way we communicate about it. Using affective and feminist materialist approaches to rhetorical criticism, Stephanie Larson examines how discourses about rape and sexual assault rely on strategies of containment, denying the felt experiences of victims and ultimately stalling broader claims for justice. Investigating anti-pornography debates from the 1980s, Violence Against Women Act advocacy materials, sexual assault forensic kits, public performances, and the #MeToo movement, Larson reveals how our language privileges male perspectives and, more deeply, how it is shaped by systems of power—patriarchy, white supremacy, ableism, and heteronormativity. Interrogating how these systems work to propagate masculine commitments to “science” and “hard evidence,” Larson finds that US culture holds a general mistrust of testimony by women, stereotyping it as “emotional.” But she also gives us hope for change, arguing that testimonies grounded in the bodily, material expression of violation are necessary for giving voice to victims of sexual violence and presenting, accurately, the scale of these crimes. Larson makes a case for visceral rhetorics, theorizing them as powerful forms of communication and persuasion. Demonstrating the communicative power of bodily feeling, Larson challenges the long-held commitment to detached, distant, rationalized discourses of sexual harassment and rape. Timely and poignant, the book offers a much-needed corrective to our legal and political discourses. |
| carnegie mellon data science masters acceptance rate: Human-Centered Data Science Cecilia Aragon, Shion Guha, Marina Kogan, Michael Muller, Gina Neff, 2022-03-01 Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns. |
| carnegie mellon data science masters acceptance rate: Big Data-Enabled Nursing Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, 2017-11-02 Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. |
| carnegie mellon data science masters acceptance rate: Data Democracy Feras A. Batarseh, Ruixin Yang, 2020-01-21 Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world's best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy. - The future of the data republic, life within a data democracy, and our digital freedoms - An in-depth analysis of open science, open data, open source software, and their future challenges - A comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychology - The democratization of Artificial Intelligence (AI), and data issues such as: Bias, imbalance, context, and knowledge extraction - A systematic review of AI methods applied to software engineering problems |
| carnegie mellon data science masters acceptance rate: Building Machine Learning Pipelines Hannes Hapke, Catherine Nelson, 2020-07-13 Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques |
| carnegie mellon data science masters acceptance rate: The Complete Guide to Capital Markets for Quantitative Professionals Alex Kuznetsov, 2006-11-22 The Complete Guide to Capital Markets for Quantitative Professionals is a comprehensive resource for readers with a background in science and technology who want to transfer their skills to the financial industry. It is written in a clear, conversational style and requires no prior knowledge of either finance or financial analytics. The book begins by discussing the operation of the financial industry and the business models of different types of Wall Street firms, as well as the job roles those with technical backgrounds can fill in those firms. Then it describes the mechanics of how these firms make money trading the main financial markets (focusing on fixed income, but also covering equity, options and derivatives markets), and highlights the ways in which quantitative professionals can participate in this money-making process. The second half focuses on the main areas of Wall Street technology and explains how financial models and systems are created, implemented, and used in real life. This is one of the few books that offers a review of relevant literature and Internet resources. |
| carnegie mellon data science masters acceptance rate: Optical Data Processing D. Casasent, 2014-03-12 With contributions by numerous experts |
| carnegie mellon data science masters acceptance rate: How Learning Works Susan A. Ambrose, Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, Marie K. Norman, 2010-04-16 Praise for How Learning Works How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning. —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching. —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues. —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book. —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning |
| carnegie mellon data science masters acceptance rate: e-Learning and the Science of Instruction Ruth C. Clark, Richard E. Mayer, 2016-02-19 The essential e-learning design manual, updated with the latest research, design principles, and examples e-Learning and the Science of Instruction is the ultimate handbook for evidence-based e-learning design. Since the first edition of this book, e-learning has grown to account for at least 40% of all training delivery media. However, digital courses often fail to reach their potential for learning effectiveness and efficiency. This guide provides research-based guidelines on how best to present content with text, graphics, and audio as well as the conditions under which those guidelines are most effective. This updated fourth edition describes the guidelines, psychology, and applications for ways to improve learning through personalization techniques, coherence, animations, and a new chapter on evidence-based game design. The chapter on the Cognitive Theory of Multimedia Learning introduces three forms of cognitive load which are revisited throughout each chapter as the psychological basis for chapter principles. A new chapter on engagement in learning lays the groundwork for in-depth reviews of how to leverage worked examples, practice, online collaboration, and learner control to optimize learning. The updated instructor's materials include a syllabus, assignments, storyboard projects, and test items that you can adapt to your own course schedule and students. Co-authored by the most productive instructional research scientist in the world, Dr. Richard E. Mayer, this book distills copious e-learning research into a practical manual for improving learning through optimal design and delivery. Get up to date on the latest e-learning research Adopt best practices for communicating information effectively Use evidence-based techniques to engage your learners Replace popular instructional ideas, such as learning styles with evidence-based guidelines Apply evidence-based design techniques to optimize learning games e-Learning continues to grow as an alternative or adjunct to the classroom, and correspondingly, has become a focus among researchers in learning-related fields. New findings from research laboratories can inform the design and development of e-learning. However, much of this research published in technical journals is inaccessible to those who actually design e-learning material. By collecting the latest evidence into a single volume and translating the theoretical into the practical, e-Learning and the Science of Instruction has become an essential resource for consumers and designers of multimedia learning. |
| carnegie mellon data science masters acceptance rate: 2012-2013 College Admissions Data Sourcebook Northeast Edition , |
| carnegie mellon data science masters acceptance rate: Practice-based Design Research Laurene Vaughan, 2017-01-26 Practice-Based Design Research provides a companion to masters and PhD programs in design research through practice. The contributors address a range of models and approaches to practice-based research, consider relationships between industry and academia, researchers and designers, discuss initiatives to support students and faculty during the research process, and explore how students' experiences of undertaking practice-based research has impacted their future design and research practice. The text is illustrated throughout with case study examples by authors who have set up, taught or undertaken practice-based design research, in a range of national and institutional contexts. |
| carnegie mellon data science masters acceptance rate: Handbook of Digital Forensics and Investigation Eoghan Casey, 2009-10-07 Handbook of Digital Forensics and Investigation builds on the success of the Handbook of Computer Crime Investigation, bringing together renowned experts in all areas of digital forensics and investigation to provide the consummate resource for practitioners in the field. It is also designed as an accompanying text to Digital Evidence and Computer Crime. This unique collection details how to conduct digital investigations in both criminal and civil contexts, and how to locate and utilize digital evidence on computers, networks, and embedded systems. Specifically, the Investigative Methodology section of the Handbook provides expert guidance in the three main areas of practice: Forensic Analysis, Electronic Discovery, and Intrusion Investigation. The Technology section is extended and updated to reflect the state of the art in each area of specialization. The main areas of focus in the Technology section are forensic analysis of Windows, Unix, Macintosh, and embedded systems (including cellular telephones and other mobile devices), and investigations involving networks (including enterprise environments and mobile telecommunications technology). This handbook is an essential technical reference and on-the-job guide that IT professionals, forensic practitioners, law enforcement, and attorneys will rely on when confronted with computer related crime and digital evidence of any kind. *Provides methodologies proven in practice for conducting digital investigations of all kinds*Demonstrates how to locate and interpret a wide variety of digital evidence, and how it can be useful in investigations *Presents tools in the context of the investigative process, including EnCase, FTK, ProDiscover, foremost, XACT, Network Miner, Splunk, flow-tools, and many other specialized utilities and analysis platforms*Case examples in every chapter give readers a practical understanding of the technical, logistical, and legal challenges that arise in real investigations |
| carnegie mellon data science masters acceptance rate: College Admissions Data Sourcebook Northeast Edition Bound 2010-11 , 2010-09 |
| carnegie mellon data science masters acceptance rate: Performance Improvement in Hospitals and Health Systems James R. Langabeer II, FHIMSS, CMA, Editor, 2009 |
| carnegie mellon data science masters acceptance rate: Advanced Analytics with R and Tableau Jen Stirrup, Ruben Oliva Ramos, 2017-08-22 Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of R About This Book A comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and R Combine Tableau analytics and visualization with the power of R using this step-by-step guide Wondering how R can be used with Tableau? This book is your one-stop solution. Who This Book Is For This book will appeal to Tableau users who want to go beyond the Tableau interface and deploy the full potential of Tableau, by using R to perform advanced analytics with Tableau. A basic familiarity with R is useful but not compulsory, as the book will start off with concrete examples of R and will move quickly into more advanced spheres of analytics using online data sources to support hands-on learning. Those R developers who want to integrate R in Tableau will also benefit from this book. What You Will Learn Integrate Tableau's analytics with the industry-standard, statistical prowess of R. Make R function calls in Tableau, and visualize R functions with Tableau using RServe. Use the CRISP-DM methodology to create a roadmap for analytics investigations. Implement various supervised and unsupervised learning algorithms in R to return values to Tableau. Make quick, cogent, and data-driven decisions for your business using advanced analytical techniques such as forecasting, predictions, association rules, clustering, classification, and other advanced Tableau/R calculated field functions. In Detail Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation. Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics. By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples. Style and approach Tableau (uniquely) offers excellent visualization combined with advanced analytics; R is at the pinnacle of statistical computational languages. When you want to move from one view of data to another, backed up by complex computations, the combination of R and Tableau makes the perfect solution. This example-rich guide will teach you how to combine these two to perform advanced analytics by integrating Tableau with R and create beautiful data visualizations. |
| carnegie mellon data science masters acceptance rate: Government Reports Announcements & Index , 1993 |
| carnegie mellon data science masters acceptance rate: CAD and Robotics in Architecture and Construction A. Bijl, O. Akin, C.-C. Chen, B. Dave, S. Pithavadian, Y. E. Kalay, A. C. Harfmann, L. M. Swerdloff, R. Krishnamurti, G. Schmitt, J.-C. Robert, J. Weeks, U. Flemming, R. Coyne, T. Glavin, M. Rychener, L. Koskela, R. Hynynen, M. Kallavuo, K. Kahkönen, J. Salokivi, A. H. Bridges, A. Polistina, W. L. Whittaker, Y. Hasegawa, C. Abel, A. H. Slocum, R. Kangari, E. Bandari, M.-C. Wanner, M. Skibniewski, P. Derrington, C. Hendrickson, R. F. Woodbury, W. T. Keirouz, I. J. Oppenheim, D. R. Rehak, C. F. Earl, N. Kano, J. L. Crowley, P. J. Drazan, B. Motazed, H.-R. Oeser, N. Tanaka, M. Saito, K. Arai, K. Banno, T. Ochi, S. Kikuchi, T. Ueno, T. Yoshida, S. Suzuki, J. Maeda, 2012-12-06 After two decades, data processing has finally, and probably forever, found its niche among civil engineering and construction (CEC) professionnals, through word processors, digitizing tables, management software, and increasingly via drawing software and computer-aided design (CAD), recently, robots have even started invading work sites. What are the main trends of CAD and robotics in the field of architecture and civil enginee ring? What type of R&D effort do university and industrial laboratories undertake to devise the professional software that will be on the market in the next three to five years? These are the issues which will be addressed during this symposium. To this effect, we have planned concurrently an equipment and software show, as well as a twofold conference. Robotic is just starting in the field of civil engineering and construction. A pioneer, the Civil Engineering Departement of Carnegie-Mellon University, in the United States, organized the first two international symposia, in 1984 and 1985 in Pittsburgh. This is the third meeting on the subject (this year, however, we have also included CAD). It constitutes the first large international symposium where CAD experts, specialists in architecture and CEC robotics will meet. From this standpoint, it should be an ideal forum for exchanging views and expe riences on a wide range of topics, and we hope it will give rise to novel applications and new syntheses. This symposium is intented for scientists, teachers, students and also for manufacturers and all CEC professionals. |
| carnegie mellon data science masters acceptance rate: Masters Theses in the Pure and Applied Sciences Wade H. Shafer, 2012-12-06 Masters Theses in the Pure and Applied Sciences was first conceived, published, and dis seminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) * at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemination phases of the ac tivity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volume were handled by an international publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 23 (thesis year 1978) a total of 10,148 theses titles from 27 Canadian and 220 United States universities. We are sure that this broader base for theses titles reported will greatly enhance the value of this important annual reference work. While Volume 23 reports these submitted in 1978, on occasion, certain universities do report theses submitted in previous years but not reported at the time. |
| carnegie mellon data science masters acceptance rate: Towards Trustworthy Artificial Intelligent Systems Maria Isabel Aldinhas Ferreira, Mohammad Osman Tokhi, 2022-09-07 This present book provides valuable insights on the technical, societal and legal challenges posed by the use of artificial intelligent systems in a plethora of different applications, from embodied robotic systems to ML algorithms. Engaging with concerns about equity, privacy, surveillance and respect for human dignity, “Towards Trustworthy Artificial Intelligent Systems” highlights the fundamental factors on which stakeholders’ trust relies, identifying benchmarking, standardisation and certification as milestones grounding and consolidating that future trust. The multidisciplinary approach followed will make this book a valuable resource for all those involved in the production and deployment of AIs, as well as for academia and legal practitioners. |
| carnegie mellon data science masters acceptance rate: Web and Network Data Science Thomas W. Miller, 2015 Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University's prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems. |
| carnegie mellon data science masters acceptance rate: Physical Metallurgy David E. Laughlin, Kazuhiro Hono, 2014-07-24 This fifth edition of the highly regarded family of titles that first published in 1965 is now a three-volume set and over 3,000 pages. All chapters have been revised and expanded, either by the fourth edition authors alone or jointly with new co-authors. Chapters have been added on the physical metallurgy of light alloys, the physical metallurgy of titanium alloys, atom probe field ion microscopy, computational metallurgy, and orientational imaging microscopy. The books incorporate the latest experimental research results and theoretical insights. Several thousand citations to the research and review literature are included. - Exhaustively synthesizes the pertinent, contemporary developments within physical metallurgy so scientists have authoritative information at their fingertips - Replaces existing articles and monographs with a single, complete solution - Enables metallurgists to predict changes and create novel alloys and processes |
| carnegie mellon data science masters acceptance rate: Information Security Management Handbook Harold F. Tipton, Micki Krause, 2004-12-28 Since 1993, the Information Security Management Handbook has served not only as an everyday reference for information security practitioners but also as an important document for conducting the intense review necessary to prepare for the Certified Information System Security Professional (CISSP) examination. Now completely revised and updated and in its fifth edition, the handbook maps the ten domains of the Information Security Common Body of Knowledge and provides a complete understanding of all the items in it. This is a ...must have... book, both for preparing for the CISSP exam and as a comprehensive, up-to-date reference. |
| carnegie mellon data science masters acceptance rate: Museums and Digital Culture Tula Giannini, Jonathan P. Bowen, 2019-05-06 This book explores how digital culture is transforming museums in the 21st century. Offering a corpus of new evidence for readers to explore, the authors trace the digital evolution of the museum and that of their audiences, now fully immersed in digital life, from the Internet to home and work. In a world where life in code and digits has redefined human information behavior and dominates daily activity and communication, ubiquitous use of digital tools and technology is radically changing the social contexts and purposes of museum exhibitions and collections, the work of museum professionals and the expectations of visitors, real and virtual. Moving beyond their walls, with local and global communities, museums are evolving into highly dynamic, socially aware and relevant institutions as their connections to the global digital ecosystem are strengthened. As they adopt a visitor-centered model and design visitor experiences, their priorities shift to engage audiences, convey digital collections, and tell stories through exhibitions. This is all part of crafting a dynamic and innovative museum identity of the future, made whole by seamless integration with digital culture, digital thinking, aesthetics, seeing and hearing, where visitors are welcomed participants. The international and interdisciplinary chapter contributors include digital artists, academics, and museum professionals. In themed parts the chapters present varied evidence-based research and case studies on museum theory, philosophy, collections, exhibitions, libraries, digital art and digital future, to bring new insights and perspectives, designed to inspire readers. Enjoy the journey! |
| carnegie mellon data science masters acceptance rate: Risk , 2001 |
| carnegie mellon data science masters acceptance rate: Statistics in the Public Interest Alicia L. Carriquiry, Judith M. Tanur, William F. Eddy, 2022-04-22 This edited volume surveys a variety of topics in statistics and the social sciences in memory of the late Stephen Fienberg. The book collects submissions from a wide range of contemporary authors to explore the fields in which Fienberg made significant contributions, including contingency tables and log-linear models, privacy and confidentiality, forensics and the law, the decennial census and other surveys, the National Academies, Bayesian theory and methods, causal inference and causes of effects, mixed membership models, and computing and machine learning. Each section begins with an overview of Fienberg’s contributions and continues with chapters by Fienberg’s students, colleagues, and collaborators exploring recent advances and the current state of research on the topic. In addition, this volume includes a biographical introduction as well as a memorial concluding chapter comprised of entries from Stephen and Joyce Fienberg’s close friends, former students, colleagues, and other loved ones, as well as a photographic tribute. |
| carnegie mellon data science masters acceptance rate: Assessment of the Department of Veterans Affairs Airborne Hazards and Open Burn Pit Registry National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Board on the Health of Select Populations, Committee on the Assessment of the Department of Veterans Affairs Airborne Hazards and Open Burn Pit Registry, 2017-03-28 Military operations produce a great deal of trash in an environment where standard waste management practices may be subordinated to more pressing concerns. As a result, ground forces have long relied on incineration in open-air pits as a means of getting rid of refuse. Concerns over possible adverse effects of exposure to smoke from trash burning in the theater were first expressed in the wake of the 1990â€1991 Gulf War and stimulated a series of studies that indicated that exposures to smoke from oil-well fires and from other combustion sources, including waste burning, were stressors for troops. In January 2013, Congress directed the Department of Veterans Affairs (VA) to establish and maintain a registry for service members who may have been exposed to toxic airborne chemicals and fumes generated by open burn pits. Assessment of the Department of Veterans Affairs Airborne Hazards and Open Burn Pit Registry analyzes the initial months of data collected by the registry and offers recommendations on ways to improve the instrument and best use the information it collects. This report assesses the effectiveness of the VA's information gathering efforts and provides recommendations for addressing the future medical needs of the affected groups, and provides recommendations on collecting, maintaining, and monitoring information collected by the VA's Airborne Hazards and Open Burn Pit Registry. |
| carnegie mellon data science masters acceptance rate: Matter and Interactions Ruth W. Chabay, Bruce A. Sherwood, 2015-01-12 Matter and Interactions, 4th Edition offers a modern curriculum for introductory physics (calculus-based). It presents physics the way practicing physicists view their discipline while integrating 20th Century physics and computational physics. The text emphasizes the small number of fundamental principles that underlie the behavior of matter, and models that can explain and predict a wide variety of physical phenomena. Matter and Interactions, 4th Edition will be available as a single volume hardcover text and also two paperback volumes. |
| carnegie mellon data science masters acceptance rate: Information Quality and Governance for Business Intelligence Yeoh, William, 2013-12-31 Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems. |
| carnegie mellon data science masters acceptance rate: Optimization for Machine Learning Suvrit Sra, Sebastian Nowozin, Stephen J. Wright, 2012 An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community. |
| carnegie mellon data science masters acceptance rate: Workers on Arrival Joe William Trotter, 2021-01-19 An eloquent and essential correction to contemporary discussions of the American working class.—The Nation From the ongoing issues of poverty, health, housing, and employment to the recent upsurge of lethal police-community relations, the black working class stands at the center of perceptions of social and racial conflict today. Journalists and public policy analysts often discuss the black poor as “consumers” rather than “producers,” as “takers” rather than “givers,” and as “liabilities” instead of “assets.” In his engrossing history, Workers on Arrival, Joe William Trotter, Jr., refutes these perceptions by charting the black working class’s vast contributions to the making of America. Covering the last four hundred years since Africans were first brought to Virginia in 1619, Trotter traces the complicated journey of black workers from the transatlantic slave trade to the demise of the industrial order in the twenty-first century. At the center of this compelling, fast-paced narrative are the actual experiences of these African American men and women. A dynamic and vital history of remarkable contributions despite repeated setbacks, Workers on Arrival expands our understanding of America’s economic and industrial growth, its cities, ideas, and institutions, and the real challenges confronting black urban communities today. |
| carnegie mellon data science masters acceptance rate: Combating Security Breaches and Criminal Activity in the Digital Sphere Geetha, S., Phamila, Asnath Victy, 2016-06-09 With the rapid advancement in technology, a myriad of new threats have emerged in online environments. The broad spectrum of these digital risks requires new and innovative methods for protection against cybercrimes. Combating Security Breaches and Criminal Activity in the Digital Sphere is a pivotal reference source for the latest scholarly research on current trends in cyber forensic investigations, focusing on advanced techniques for protecting information security and preventing potential exploitation for online users. Featuring law enforcement perspectives, theoretical foundations, and forensic methods, this book is ideally designed for policy makers, analysts, researchers, technology developers, and upper-level students. |
| carnegie mellon data science masters acceptance rate: Analytics of Life Mert Damlapinar, 2019-11-11 Analytics of Life provides the reader with a broad overview of the field of data analytics and artificial intelligence. It provides the layperson an understanding of the various stages of artificial intelligence, the risks and powerful benefits. And it provides a way to look at big data and machine learning that enables us to make the most of this exciting new realm of technology in our day-to-day jobs and our small businesses. Questions you can find answers* * What is artificial intelligence (AI)? * What is the difference between AI, machine learning and data analytics? * Which jobs AI will replace, which jobs are safe from data analytics revolution? * Why data analytics is the best career move? * How can I apply data analytics in my job or small business? Who is this book for? * Managers and business professionals * Marketers, product managers, and business strategists * Entrepreneurs, founders and startups team members * Consultants, advisors and educators * Almost anybody who has an interest in the future According to an article by Cade Metz in The New York Times, Researchers say computer systems are learning from lots and lots of digitized books and news articles that could bake old attitudes into new technology. Oxford University professor Nick Bostrom argues that if machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control. MIT professor Max Tegmark describes and illuminates the recent, ground-breaking advances in Artificial Intelligence and how it might overtake human intelligence. As Oxford University economist Daniel Susskind points out, technological progress could bring about unprecedented prosperity, solving one of humanity's oldest problems: how to make sure that everyone has enough to live on. Distinguished AI researcher and professor of computer science at UC Berkeley, Russell Stuart suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Industry experts claim that AI will have a negative impact on blue-collar jobs, but Mert predicts that Americans and Europeans will experience a strong impact on white-collar jobs as well. And Mert also provides research results and a clear description of which jobs will be affected and how soon, which jobs could be enhanced with AI. Analytics of Life also provides solutions and insight into some of the most profound changes to come in human history. |
| carnegie mellon data science masters acceptance rate: Cass & Birnbaum's Guide to American Colleges Melissa Cass, 1994 This invaluable guide presents complete information on college admission policies, academic requirements, and campus life. This 16th edition features an all-new College Selection Index that guides prospective students through the difficult process of selecting the right college. The most useful of all.--Harvard Educational Review. |
Andrew Carnegie - Wikipedia
Andrew Carnegie (English: / kɑːrˈnɛɡi / kar-NEG-ee, Scots: [kɑrˈnɛːɡi]; [2][3][note 1] November 25, 1835 – August 11, 1919) was a Scottish-American industrialist and philanthropist. Carnegie led …
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May 23, 2025 · Andrew Carnegie (born November 25, 1835, Dunfermline, Fife, Scotland—died August 11, 1919, Lenox, Massachusetts, U.S.) was a Scottish-born American industrialist who …
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Andrew Carnegie (1835–1919) was among the most famous and wealthy industrialists of his day. Through the Carnegie Corporation of New York, the innovative philanthropic foundation he …
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Carnegie Corporation of New York, which Andrew Carnegie (1835–1919) established in 1911 “to promote the advancement and diffusion of knowledge and understanding,” is one of the oldest …
Andrew Carnegie - Wikipedia
Andrew Carnegie (English: / kɑːrˈnɛɡi / kar-NEG-ee, Scots: [kɑrˈnɛːɡi]; [2][3][note 1] November 25, 1835 – August 11, 1919) was a Scottish-American industrialist and …
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Apr 1, 2019 · Sign in to My CL to access Carnegie Learning's MATHia Software, Teacher's Toolkit or Educator, Parent, or Student Resource Center …
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Carnegie designs and manufactures a suite of fully-customizable, remarkably effective, and radically sustainable acoustic solutions that will help keep the noise down and style factor up …
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The Carnegie Endowment for International Peace generates strategic ideas and independent analysis, supports diplomacy, and trains the next generation of scholar-practitioners …
